Fundamentals of pattern analysis
for classical Chinese medicine (CCM)
part 4

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Fundamentals of pattern analysis
for classical Chinese medicine (CCM)

part 4:
The art, logic, & mathematics

by Roger W. Wicke, Ph.D. (creator of  HerbalThink-TCM
and Director of Rocky Mountain Herbal Institute),

in collaboration with Curt Kruse, M.S.  &  C.S. Cheung, M.D.
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2021 Dec 01
(updated 2023 Jan 13)


by the





[[[Click on the link shown at right.
The window that pops up will be used to display links to diagrams, tables, or references throughout this lecture.]]]

    >> Create graphics/references window



I (Roger Wicke) am not a medical doctor, though I do have a PhD in biomedical engineering — MIT, 1980. The information I will be presenting in these lectures

  • is educational and general in nature
  • should not be construed as medical advice
  • is not intended for the purpose of diagnosing, treating, curing, or preventing any disease

Individuals desiring help for specific health problems should seek advice from qualified professionals.


The art, logic, & mathematics
of pattern analysis:

* 10-D vector-space model
* AutoSage-TCM — an expert system ("AI") for generating numerically quantifiable analyses of complex clinical cases.


The 3-dimensional model for the Eight Principal Patterns (ba gang), described in lecture #3 of this series, is relatively crude and does not adequately represent the full level of detail encompassed by advanced CCM theory and its 120 syndrome-patterns. The following is a short list of a few ways that the Eight-Principal-Patterns theory can be expanded:

  • Deficiency can manifest as Deficiency of Qi, Yang, Yin, and/or Blood:
    • Qi is the body's potential for creating energy and activity (metabolism); in a larger sense, it is the functional potential (as contrasted with substance) of the body tissues and Organs. Deficiency of Qi is an inadequacy of this potential and commonly results in the symptoms of fatigue and lack of motivation. In fact, even the Organs of CCM are defined to have specific sets of functions, in contrast with Western medicine which first defines the organs as specific anatomical objects and then attempts to determine what functions those organs perform.
    • Deficiency of Yang is roughly equivalent to Deficiency of Qi combined with Interior-Cold and results in the inability of the body to activate and warm itself.
    • Yin represents substance, calmness, and quiescence, and because 80% of the body is constituted by water, Fluids are an important aspect of Yin. Deficiency of Yin results in an inability of the body to remain calm, relaxed, and fully hydrated; dehydration often leads to overheating, low-grade fevers, and mental agitation.
    • Blood, in CCM, nourishes and moistens the tissues. Having the qualities of liquid, it is Yin in nature. While similar to the blood of medical physiology, it is not exactly identical. Deficiency of Blood may result in atrophy of body tissues, loss of muscle mass, general weight loss, and anemia.
  • Excess can manifest as overabundance, accumulations, stagnancy, or blockages of Qi, Blood, and Fluids:
    • An overabundance of Qi can result in symptoms of hyperactivity, mental agitation and manias, inability to relax, high blood pressure, and hyper-functioning of specific Organs. People with an overabundance of Qi and a strong constitution can remain healthy if they engage in vigorous exercise, outdoor activities or professions, and maintain a healthy mental/spiritual outlook.
    • Dampness results when Fluids accumulate abnormally; such accumulations can result from blockages, stagnancy, or non-harmonious movement of Qi and Blood and from dietary imbalances like overconsumption of sweet foods.
    • Stagnancy and/or Reflux of Qi can result when the harmonious function of the Organs is disturbed. Disharmonies of the Liver are especially prone to inducing Stagnancy of Qi. In cases where the circulation of Qi is markedly disturbed, it may flow in abnormal directions (Qi Reflux), resulting in symptoms of nausea, vomiting, hiccoughing, and coughing.
    • Stagnancy of Blood can result from chronic Stagnancy of Qi, chronic inflammation, inactivity, and physical blockages such as prolonged, excessive pressures or muscle tension within specific tissues, and inadequate blood flow. It can be localized to specific body locations, regions, and Organs, or it can be generalized to the whole body. Ecchymosis, or blood clotting, can result from Stagnancy of Blood or as the consequence of abnormal bleeding.
    • Interior Wind results in neurological symptoms of spasms, tics, tremors, and tinnitus. Interior Wind is usually associated with other Internal patterns of disharmony and is considered to be a Branch pattern of these other disharmonies; though it has the quality of Excess, its Root pattern(s) may be of either an Excess or a Deficiency nature. Because the Liver is responsible for smooth, harmonious movement of Qi in the body, disruption of this function may lead to Interior Wind; Interior Wind is often a Branch pattern of a Root disharmony of the Liver.
    In cases of Excess, the pulse will generally be stronger than normal at one or more of the standard positions at the radial artery. (See reference.)
  • Interior/Exterior can be further augmented by specifying the body sector and Organ(s):
    • The internal Organs are distributed among Three "Burners", which represent a superior/inferior (up/down) dimension anatomically:
      • Upper Burner: Heart, Lungs. CCM theory describes the Upper Burner as being like a mist, which is appropriate given that its Organs are intimately involved with respiration and circulation — the activation of circulating Blood with Qi inhaled by the Lungs.
      • Middle Burner: Spleen, Stomach, Liver, Gall Bladder. The Middle Burner is like a cookpot; it governs digestion and assimilation of nutrients.
      • Lower Burner: Small Intestine, Large Intestine, Kidneys, Urinary Bladder. The Lower Burner is like a swamp; it governs the separation of the pure from the impure, retaining the former and discharging the latter.
    • Left vs. Right: certain Organs/entities can be classified by their laterality. For example, the Heart is clearly within the left side, the Gall Bladder on the right. Most Organs will be classified nearer the midline, including those which are located bilaterally, like Lungs and Large Intestine. Laterality is especially important when evaluating the significance of abnormal sensations and localized pain.

The preceding schema can be represented by the compact mathematical notation outlined in this table, which effectively defines a 10-dimensional vector space. The first 3 vector components specify the location/locus within the body, and the last 7 components represent various qualities present at that locus. ("Locus" in the context of CCM is more of a functional attribute rather than strictly anatomical.)


    >> 10-D vector-space model

    >> Reference 4-bpulse positions

Most of the syndrome patterns currently defined in classical Chinese medicine came into common use by herbal doctors by the late 19th century, before the era of modernization and industrialization. Those patterns represented common illness syndromes brought on by extremes in weather and climate, lack of adequate food, lack of sanitation, overwork and emotional stress. Industrialization introduced a wide range of harmful and toxic influences rarely or never experienced before. While populations began to experience greater health and longevity due to increased availability and variety of food, vastly improved sanitation from plumbing systems and refrigeration, and awareness of personal hygiene (see ref. 4-c) — at the same time they became subject to an increasing array of toxic industrial chemicals, electromagnetic and ionizing radiations, and the novel stresses of living in densely populated urban centers. While the syndrome patterns defined by the early Chinese doctors were still as valid as ever — these syndromes are fundamental to the nature of human life, regardless of circumstances — people began to experience more complex combinations of these syndromes.

A very general list of environmental hazards and toxic factors known to cause ill health and disease is shown here. Those factors highlighted in orange have increased significantly in industrialized nations during the 20th century, many of them by orders of magnitude. For example, exposure to microwave radiation in major cities of the world has increased by thousands and even millions of times following the mass introduction of radio, television, and cell phones. To ignore these factors while administering only herbal formulas to modern patients is a major reason for lack of results. In my experience, the more complex a clinical case, the greater is the likelihood that multiple environmental hazards are involved and must be mitigated before progress can be made.

Because of this increased complexity, it is now quite common for people in industrialized nations to manifest many multiple syndrome-patterns simultaneously, even though each syndrome may manifest to only a mild degree, making accurate diagnosis extremely challenging. While accurate traditional diagnosis has always been acknowledged to be a skill that only the most experienced and persistent master herbalists ever achieve, this task is now more difficult than ever, and many in our profession have reverted to the unfortunate habit of choosing remedies based solely on the medical diagnosis.


    >> Environmental & lifestyle factors in illness

    >> Reference 4-c20th-century decline in childhood mortality — vaccines??

To grapple with these modern challenges and complexities, we must be absolutely clear in our minds about the rules, or axioms, governing the logic of pattern analysis:

  1. Syndromes are defined as clusters of symptoms and signs. The symptoms and signs (palpated radial pulse characteristics, tongue appearance, physical appearance, etc.) manifesting at a specific time or within a specific time period comprise the primary evidence that will determine whether specific syndromes are present and to what severity. The syndromes themselves are defined as clusters of symptoms and signs; while medical tests like analysis of blood and urine, x-rays, detection of microbial pathogens, etc. may provide interesting data that may be correlated to varying extents with symptoms and symptom clusters, in CCM the symptoms and signs are the ultimate reality, unlike in Western medicine where symptoms and other subjectively observed phenomena take a back seat to presumably objective-definitive lab tests. In my experience, it has been the rule rather than the exception that symptoms and symptom patterns appear well before — sometimes years before — a patient's condition is medically diagnosed, so this axiom is quite sensible. For thousands of years, doctors have been relying primarily on symptoms and directly perceivable signs as the primary clues for assessing illnesses and determining courses of action. Consequently, it's my contention that symptom-pattern analysis has been vastly under-utilized as a tool for evidence-gathering and research in epidemiology, environmental medicine, and forensics. Toward the end of this lecture, I'll show you exactly how the AutoSage-TCM expert system provides a detailed, numerically quantifiable and highly sensitive "fingerprint" representation of a patient's condition.
  2. The specific way that a given syndrome may manifest in a patient is most realistically modeled as a random process. While the textbook definition of each syndrome may give the impression of a neat-and-tidy, all-or-nothing proposition, the reality is that the manner in which a syndrome unfolds is highly variable. Almost any symptom of the subset of symptoms in the definition may appear first, followed by other symptoms and an increase in severity of existing symptoms as the syndrome severity increases. In certain special cases, there may be a tendency for some symptoms to appear in a certain order (e.g., nausea generally precedes vomiting — the latter might be considered as a more severe manifestion of the former); however, in many cases there is no set pattern for their order of appearance.
  3. More than one syndrome, even many syndromes, may manifest simultaneously. The first task of any herbalist or expert system should be to estimate the relative severity of each syndrome and the probability that it truly describes a component of the case. In practical terms, the accuracy of the analysis is verified if it leads to a successful herbal strategy, though there are many other factors that must be considered, especially in research: placebo effect; efficacy and strength of action of specific selected herbs; patient compliance; dietary and environmental toxic exposures, especially if ongoing; etc. If done correctly, CCM pattern analysis and herbal strategy should consistently lead to high rates of success (>90%) in contrast to the popular strategy of simply choosing remedies reputed to be "good for medical disease X"; this latter habit frequently works no better than throwing darts at a target while wearing blindfolds. (Less commonly, when there is a strong correlation between the specific CCM pattern analysis and medical disease, one might get lucky.)
  4. Single symptoms or medical diagnoses cannot generally provide reliable guidelines for CCM herbal strategy. A specific symptom or sign manifesting in a case often constitutes part of the definitions for multiple syndromes; thus, the presence of a single symptom, without considering its context, generally cannot be used to make definitive conclusions about anything except a list of possibilities, and this list of possibilities is often quite lengthy. Biomedically defined diseases, like asthma, hepatitis, etc., comprise an entirely different system of analysis that often has only tenuous correlations with CCM syndrome assessment; therefore, like single symptoms, biomedical diagnoses generally cannot be used to make definitive conclusions within the CCM domain about anything except a list of possibilities.
  5. Context is everything. To determine whether the symptoms and signs that constitute a complete case report reliably point to specific syndromes requires us to always consider each syndrome candidate only within the total context of all the manifesting symptoms and signs. The German word gestalt captures this idea perfectly.
  6. The criterion for adequate symptom-sign data is syndrome uniqueness and elimination of ambiguity. To reliably conclude that a specific syndrome is present, the list of manifesting symptoms and signs must include a subset that uniquely points to that syndrome and no other. If there exists at least one manifesting symptom or sign that results in uniqueness, we can conclude that the syndrome is likely to be truly present and is a valid descriptor for at least a partial aspect of the overall state of health. Additionally, the more symptoms present that confirm this uniqueness, the greater the confidence we should have in this conclusion.
  7. Syndromes function as abstract descriptors, like colors in a painting. In principle, any clinical case may be represented by a set of one or more syndromes in much the same way that colors in a painting are used to construct an image of reality. Each syndrome represents an abstract quality that may be either present to varying degrees or absent entirely from a specific case. Unlike medical disease diagnosis, CCM syndrome assessment assumes that any arbitrary case may be described by a single syndrome or, more commonly, a combination of several syndrome-patterns from a set of defined possibilities; this is a precondition for the set of syndrome possibilities to constitute a relatively continuous vector space (in contrast to the diagnostic domain of Western biomedicine, which contains vast regions that are undefined or highly ambiguous), which theoretically encompasses all possible clinical manifestations. Another way of stating this is that the set of 120 CCM syndromes comprises the body's repertoire of adaptive responses to various stresses and hazards — for example, fever as a means of amplifying specific immune responses to infection; shivering and constricting blood flow to the periphery in response to cold weather (or diminished metabolic energy) in order to conserve metabolic heat. For these reasons, the ancient art of CCM pattern analysis will likely remain a useful medical tool far into the future, regardless of human technological advances and Star-Trek type civilizations that have been foreseen by some.
  8. Resolving critical clinical ambiguities is crucial for an accurate assessment and a successful clinical strategy. Whenever a specific subset of symptoms and signs points to multiple syndrome possibilities, we should acquire more information in order to resolve the ambiguity and reliably pinpoint one of the syndrome possibilities as the most likely answer. In doing this task, it is essential to differentiate syndromes that are very different from each other (e.g., Deficiency of Spleen Qi vs. Spleen Damp Heat) and that require quite different herbal strategies; it is less crucial to differentiate similar syndromes (e.g., Deficiency of Spleen Qi vs. Deficiency of Spleen Yang), which require similar herbal strategies. Data acquired from tongue inspection and radial pulse palpation are generally among the most useful categories of data in resolving critical clinical ambiguities.

The vast majority of student and practitioner errors in pattern analysis inevitably involve violation of one or more of the preceding axioms. During the early 1990's, my colleagues and I first seriously conceived of constructing expert system software to rigorously enforce adherence to these rules in order to achieve accurate automated pattern analysis — to serve both as a teaching tool and a clinical tool to handle the many complex cases that were becoming so common in industrialized nations and which only a tiny percentage of CCM practitioners could successfully handle.


Fundamental axioms of syndrome-pattern analysis

  1. Syndromes are defined as clusters of symptoms and signs.
  2. The specific way that a given syndrome may manifest in a patient is most realistically modeled as a random process.
  3. More than one syndrome, even many syndromes, may manifest simultaneously.
  4. Single symptoms or medical diagnoses cannot generally provide reliable guidelines for CCM herbal strategy.
  5. Context is everything.
  6. The criterion for adequate symptom-sign data is syndrome uniqueness and elimination of ambiguity.
  7. Syndromes function as abstract descriptors, like colors in a painting.
  8. Resolving critical clinical ambiguities is crucial for an accurate assessment and a successful clinical strategy.

To date, the vast majority of expert systems for Chinese medicine have been relatively crude affairs, capable of merely identifying the single dominant syndrome pattern, typically the one that matches the greatest number of symptoms in a case. However, for the complex cases characterized by diverse multiple syndromes that have become so common in industrialized nations, something much more is required.

The remainder of this lecture comprises an introduction and overview of RMHI's AutoSage-TCM expert system, completed in 2017 and now fully integrated into our curriculum.


    >> AutoSage-TCM schema

In the first step of the AutoSage-TCM process, the practitioner takes the patient's symptom history and enters in the symptom-sign data using a program called CaseQuery. CaseQuery outputs a standardized, encoded file containing all the symptoms — including optional modifier terms like severity, chronic/acute, body sector or location, time of day, time of menstrual cycle, time of year, aggravated/relieved by, etc. — plus detailed tongue and pulse descriptions.

Technical note:   AutoSage-TCM employs fuzzy logic — as long as the CaseQuery user specifies symptoms that are "in the right ballpark", these will ultimately contribute toward an accurate pattern analysis. The closer the individual symptom to that specified by an archetypal pattern definition, the greater the contribution of that symptom to the importance that the inference engine assigns to that pattern. Thus, while CaseQuery allows a fine level of detail to be recorded, AutoSage-TCM is quite tolerant of the normal variations, ambiguities, and overlapping of meanings inherent in human language.

Over 500 common symptoms are available to choose from, organized by category and subcategory. In this panel, #2, we see under the subcategory  Thermal perceptions  that the user has selected the symptoms  dislikes heat  and  hot flushes .

 4-f    CaseQuery

    >> CaseQuery: symptom selection

The exact meaning of each selected symptom may be further refined by associating specific modifier terms. In panel #12, the user has specified that the symptom of  dislikes heat  is  severe  and  chronic .

In the bottom frame,  Output display , we can examine the fully encoded version of the symptoms and any associated modifiers. It is this output that will then be submitted to  AutoSage-TCM  expert system for analysis.


    >> CaseQuery: symptom modifiers

In panel #13, various tongue tissue and tongue coating features may be specified. Here, the user has selected two different shades of tongue tissue color. In the next panel, #14, the user will be able to specify the tongue sectors to which these colors apply.


    >> CaseQuery: tongue features

Here the user has specified that tongue tissue color  red_ns  applies to all sectors in row 'a', which is at the tip of the tongue. On the right is a schematized map of all tongue sectors, and the three selected sectors in row 'a' are highlighted in blue. (I've drawn a dotted-line rectangle around this map.)


    >> CaseQuery: tongue sectors

This diagram displays the precise location of each sector on the tongue surface.


    >> CaseQuery: tongue sector map

In panel #17, a detailed pulse description has been entered. Parameters at the top apply to the pulse regardless of position. Below this, position-dependent qualities are entered for each of six positions, three at the left radial pulse and three at the right.


    >> CaseQuery: pulse parameters

The Pulse Simulator module is a video simulation tool than enables users to specify any of a possible 900 million distinct pulses and to visualize these pulses in three dimensions and time. Displayed in this first example is an entirely normal pulse — each of its 12 parameters is normal.

In the vast majority of cases, a pulse will be felt most strongly at a specific level, which indicates its Depth; you should then note all its other parameter values at this Depth. If you gradually decrease or increase pressure of the palpating finger, the pulse will gradually fade in strength but all the other qualities will not significantly change.

The Pulse Simulator has enabled RMHI to teach students the art of traditional pulse palpation in a fraction of the time we formerly required. Many students worldwide have found learning this art to be exceedingly challenging due to the conflicting terminology in common use and the lack of discipline and standards among both teachers and students. RMHI's pulse criteria are closely consistent with Li Shi Zhen's classic text, Pulse Diagnosis.

 4-l    Pulse Simulator

    >> Normal pulse

    >> Reference 4-lLi Shi Zhen

This second pulse example is a bowstring pulse, which is one of the 28 classical pulse archetypes described in most traditional texts of Chinese medicine.


    >> Bowstring pulse

Real life, however, rarely matches textbook examples exactly. With 12 different parameters and from 4 to 7 different values selectable for each parameter, this simulation software can display several hundred million distinctly different pulses — and experienced practitioners with adequate sensitivity in their fingertips can accurately distinguish these differences.

Displayed in this last example is a pulse that might occur in a patient with severe Stagnation of Heart Blood plus Heart Phlegm Fire.


    >> A complex pulse typical of severe Stagnation of Heart Blood plus Heart Phlegm Fire

The AutoSage-TCM inference engine is the heart of the expert system. It applies a knowledge base comprising the accumulated body of historical diagnostic definitions and rules to the symptom data. Rather than merely identifying the single dominant pattern, AutoSage systematically determines magnitude, rank, and probability for each of the 120 syndromes in the knowledge base, identifying all dominant and secondary patterns. Additionally, a detailed breakdown of the inference engine's reasoning for each syndrome is accessible to the user.

In the final portion of this lecture, we will examine two clinical cases that used the AutoSage-TCM system to provide the analysis.

 4-o    AutoSage-TCM

    >> AutoSage-TCM schema

In this panel, you see the list of symptoms for case #1 in standardized encoded format as output by the CaseQuery utility and summarized here in the Autosage-TCM report.

Over a period of several years, I had provided consulting services to former students and RMHI graduates in three very similar cases occurring during epidemics of hemorrhagic fever, each in various tropical countries. The symptoms listed here are a composite, or a sort of average, of these three cases.

In each case, the practitioner sought advice after hospital physicians had declared all the administered antibiotics a failure and the patient likely to die within days. In each case, standard herbal formulas and protocol for Ying-stage syndrome-patterns were then administered, with only slight modifications, and fevers of over 105 deg.F. diminished to under 100 deg.F. — 40.5 to 38. deg.C. — within 3 to 12 hours. Other symptoms also resolved (including one case of imminent kidney failure associated with dengue fever), and the patient was released from the hospital. All three cases recovered fully within another week.

 4-p    Case #1

    >> Case #1: symptoms

Here we see the pulse data as summarized in the Autosage-TCM report, in the format that all our students learn by using the Pulse Simulator.

The pulse data in most positions can be summarized as being in the ballpark of rapid-sinking-slippery, except in position L2 (left guan), which corresponds to Liver/GallBladder in the CCM system. This pulse is entered on two lines, because the quality changes quite radically with depth. Superficially, it is similar to a classical bowstring pulse, but as pressure is applied, it abruptly shifts to a markedly slippery quality. In my course material, I often refer to such two-level pulses as "Jekyll and Hyde" pulses. These are relatively uncommon, but they do show up on occasion, and when they do appear, this is often of major significance.


    >> Case #1: pulse data

In this panel we see that AutoSage-TCM correctly identifies the two very similar textbook patterns that most closely match the symptoms and signs of case #1.

In this view of the analysis, all syndromes are grouped by quality, so that similar syndromes are grouped together. The dominant syndromes, as determined by the product of the magnitude, rank, and probability values for each syndrome — see table at right for explanation — are highlighted in green and preceded by a green checkmark . Syndromes preceded by a blue checkmark are in the second tier of syndromes.

At the top, we see a line stating that the  Complexity Score  has a value of 1.37. Relatively simple cases, for which all the dominant syndromes are in the same "ballpark" (are close to each other in our 10-D vector-space model), typically have values of 1.5 or less. For similar syndromes, similar herbal formulas are appropriate.

When a single syndrome-pattern (or a small number of very similar syndromes, as in this case) clearly dominates, uncomplicated by secondary syndromes of a quite different nature, the herbal textbooks point to a standard class of Chinese herbal formulas for such cases. Such cases are said to be simple, merely because the pattern assessment is clear; however, this implies nothing about the relative severity of such cases, which can range from the benign to the life-threatening.

The Pattern analysis summary displayed here provides a detailed, numerically quantifiable and highly sensitive "fingerprint" representation of a patient's condition. Selected subsets of this data may be used to calculate statistics for use in fields as diverse as epidemiology, environmental medicine, and forensics.

AutoSage-TCM is not really needed for analyzing simple cases, since practitioners who know their textbook pattern definitions well will be able to identify the correct pattern without difficulty. We start with such a case, though, to introduce you to the basic features of AutoSage-TCM and to demonstrate that it performs as expected.


    >> Case #1: pattern analysis

Magnitude (MAGN), Rank, and
Probability (PROB) explained.

MAGN answers the question "Assuming that a syndrome is actually present (has a high PROB value), how severe is this syndrome, on a scale from 0-7?"
  MAGN increases in value with the percentage of symptom variables in the syndrome definition that are matched by symptoms actually present; it also increases in value as the qualifying symptoms become severe or extreme. Fuzzy-set specifications for each symptom variable provide for the possibility of a partial match in each instance. If all symptom variables are matched with a severity value of 'moderate', the MAGN value would be 7.0, because a scaling factor of 7 is applied.
Syndromes with the highest RANK values potentially account for the greatest number of the patient's symptoms, especially if their PROB values are also relatively high.
  RANK is an intermediate value that is used to calculate PROB. A syndrome's RANK is approximately equal to the number of symptom variables in its definition that are matched by symptoms and signs actually present, adjusted by veto factors to suppress spurious results based on fundamental criteria for Heat/Cold/Excess/Deficiency. Fuzzy-set specifications for each symptom variable provide for the possibility of a partial match in each instance. If a specific symptom has met the 'moderate' threshold for contributing to the RANK, the RANK does not increase in value with severe or extreme symptom magnitudes — these latter will increase the MAGN but not the RANK or PROB estimates.
What is the PROB (probability) that this syndrome (the "evaluated syndrome") is actually present, regardless of its MAGN and RANK scores?
  To calculate PROB, the RANK of the evaluated syndrome is compared with the Competitor Rank (CRANK) scores of all other syndromes ("competitor syndromes"); the latter are calculated by using only those symptoms significant to the definition of the evaluated syndrome, weighted by their relative importance for the evaluated syndrome. This algorithm effectively determines whether one or more competitor syndromes possibly explain the preceding subset of symptoms better than the evaluated syndrome does. In general, the greater the number of high-scoring competitor syndromes, the lower will be the PROB estimate for the evaluated syndrome.
Product of MAGN * RANK * PROB:   The dominant syndromes will be those that simultaneously have a relatively high magnitude, and explain the greatest number of the individual's symptoms, and have a high probability of being valid descriptors of at least partial aspects of the overall state of health. The single metric that best reflects this is the multiplication product of all three values.

If the user clicks on any syndrome listed in the analysis, this is typical of what they will see. First, the magnitude, rank, and probability values for that syndrome are displayed again. Then, the textbook definition appears in the form of an encoded equation. Most users familiar with the textbook definition will have no problem recognizing all the variables.

Immediately below the pattern definition are listed the  Active symptom variables , which are those that have a non-zero value. Those variables with the highest values appear preceded by a large, dark green dot.

And finally, in the  Competitor syndromes  section, the 10 closest competitor syndromes are listed, which are those syndromes that might explain some or perhaps many of the symptoms listed under  Active symptom variables . The rank values of the competitor syndromes are used to calculate the probability value for the syndrome being evaluated — for math geeks, refer to Bayes' theorem of statistical inference. The more competitor syndromes there are with high values, the lower the probability will be for the evaluated syndrome — the red dots signify that these are inhibitory influences. In this case, none of the competitor syndromes have high values, because none explains the  Active symptom variables  nearly as well as the evaluated syndrome, YingWetHeat (Ying-stage Wet Heat).

Technical note on Bayes' rule:   In real life, and in fields like operations research, decisions are ideally made in order to maximize the likelihood of desirable outcomes. Maximizing the likelihood of "being technically correct" is not actually the most desirable goal in most cases. In health care, a more realistic and desirable goal is to maximize the expected value of overall benefits vs. risks — which means being especially alert to possible contraindications. Such algorithms can be implemented by means of modified Bayesian inference, such that the a priori probabilities of each possibility are multiplied by a cofactor that is proportional to the consequences of misidentification — which can be readily estimated by determining the distance between the evaluated syndrome and the competitor syndrome under consideration. The higher the negative consequences, the higher should be the weighting factor applied to the a priori probability, and this is a brief description of the design principle underlying the AutoSage-TCM algorithm for calculating PROB.

If you are curious to explore the actual AutoSage-TCM report for case #1, see the "Reference" link shown here. We have not yet mentioned the tongue data, which is included in that report, along with detailed analyses of all 120 syndromes. (For example, why has Deficiency of Heart Yin received an overall score of "0.0", in spite of the fact that quite a few symptoms in this case match the definition? Hint: examine the competitor syndromes.)


Case #1 — detailed analysis of the dominant syndrome:

    >> Pattern definition
    >> The evidence quantified
    >> Reference: Complete AutoSage report for Case #1

    >> Reference 4-sBayes' rule

An increasing number of people are now experiencing complicated symptom pictures that do not clearly match any textbook pattern. These are typically people who may have received conflicting medical diagnoses from a series of doctors who have prescribed multiple pharmaceutical drugs and therapies. Many of these people also suffer from exposure to multiple environmental toxins, dietary poisons, EMF radiation, and other harmful factors. Designing systems to analyze such cases has been exceedingly challenging and the vast majority of TCM expert systems have succeeded in identifying only the single dominant pattern, which falls far short of what is really necessary in such cases.

If you are an experienced CCM practitioner, see if you can identify the predominant syndrome in this case by examining the list of symptoms here.

 4-t    Case #2

    >> Case #2: symptoms

Notable in the pulses are qualities that closely match a classical slippery pulse in positions L1, L2, and R1. Positions L3 and R2 have a somewhat bowstring quality; L3 is also quite floating — felt predominantly near the surface. R3 is weak and floating.


    >> Case #2: pulse data

Several years before I completed the AutoSage-TCM system, this case had baffled me. Though the individual was only moderately debilitated and though the multiple TCM syndrome patterns present were mild, these patterns were persistent and seemingly resistant to various changes in diet, personal habits, and multiple herbal strategies. For many years, it had been suspected that parasitosis (in this case, the syndrome JueYin Parasitic Evil) was at least a partial factor. However, because of the confusing combination of syndromes — spanning the range of Interior Heat to Cold, both Excess and Deficiency, with multiple Organ systems involved, when several different formulas for JueYin Parasitic Evil, including many different anti-parasitic herbs, were tried without result, I had assumed that other factors were more important. Yet those, too, failed to have any effect. In 2017, this case was one of the first cases that I used to test AutoSage-TCM. When I saw the result, I was faced with the possibility that CCM protocols had simply failed here.


    >> Case #2: pattern analysis

I traced the expert system's reasoning and could find no errors. If you are curious to examine the conclusions and the evidence for yourself, the "Reference" link shown here will take you to the complete analysis report.

When the correct herbal formula was finally determined, it had an almost immediate effect. Within one hour, more than half of the symptoms resolved and the patient finally slept better that night than he had in many years. To read the surprising details and the important lessons that this case exemplifies, follow the last link shown here.


Case #2 — detailed analysis of the dominant syndrome:

    >> Pattern definition
    >> The evidence quantified
    >> Reference: Complete AutoSage report for Case #2
    >> Reference: How Case #2 was finally resolved

  • Can automated pattern analysis provide detailed, numerically quantifiable "fingerprint" representations of one's overall health status? Might this be useful in fields as diverse as epidemiology and forensics?

The total set of 120 patterns, each with its magnitude, rank, and probability values, comprises the first part of this fingerprint that I hinted at in the introduction to this lecture series and is analogous to the total set of values for the relative position, mass, and size of each star within a star cluster or galaxy, and the probability values for whether each specific star really exists — and is not an optical illusion or detection error.

The second part of this fingerprint comprises a global description of the set of patterns: the center-of-gravity and the Complexity Score, which is the degree of dispersion about this center-of-gravity. Simple cases are comprised of a small number of significant patterns tightly distributed within a cluster. Complex cases are like larger star clusters distributed over a wide region of space — except that here we are operating within the 10-D vector-space of CCM rather than the 3-D space of the material universe.

In summary, AutoSage-TCM is a revolutionary system for providing accurate, quantitative estimates of the magnitude, rank, and probability of each of the multiple dominant syndromes that may coexist in a complex case, greatly decreasing guesswork and uncertainty from the CCM diagnostic protocol. Its detailed analyses have potential applications to fields as diverse as epidemiology, environmental medicine, and forensics.

Technical note:   AutoSage-TCM was designed to take advantage of multiple established expert-systems methods and design architectures; it is most accurately characterized as a hybrid expert system. Its pattern recognition algorithm has more similarities to case-based pattern matching and to neural-net algorithms with their parallel-processing of multiple simultaneous excitatory and inhibitory inputs than to the relatively simplistic if-then rules (decision trees) typically employed in rule-based systems. Such neural-net-like, case-matching rules allow new archetypes to be seamlessly added to the knowledge base without any reprogramming or alteration of the inference engine, in much the same manner that neural nets have the ability to integrate new knowledge into the system with ease. Additional insights and precision are achieved by modeling all syndrome-pattern relationships within the framework of an 10-dimensional vector space derived directly from traditional Chinese pathophysiology theory. This 10-D model allows the inference engine to quantitatively evaluate the relationships between pairs and groups of syndromes and the overall complexity of a given case analysis — via intermediate calculations of first moment and second central moment of the set of all syndrome vectors. The inference engine calculates probability estimates for each of the 120 syndrome patterns defined in the knowledge base by invoking Bayes' theorem of statistical inference and by using fuzzy sets to accommodate uncertainty and variable overlap in meaning of symptom-sign terms.
The fingerprint: 3-D star clusters vs.
the abstract 10-D pattern space for CCM.

3-D:   A star-cluster/galaxy10-D:   CCM pattern-space
Properties of each star in a cluster:Properties of each syndrome-pattern for a patient:
3-D position10-D position
Real or an illusion?Probability
Properties of the cluster:Properties of the patient's total set of significant syndromes:
Center of gravity of the entire star clusterCenter of gravity of all significant patterns
Square root of the 2nd central momentComplexity Score — how widely scattered are the dominant patterns?


    >> Reference 4-xcenter of gravity, 2nd central moment

In RMHI's Level-2 course, Supervised Clinical Studies, students work through their own clinical cases using both CaseQuery and AutoSage-TCM. They first make their own best effort at a pattern analysis, before receiving the AutoSage-TCM report and, then, grade and comment on their own analysis by comparing the two sets of conclusions.

Unlike most corporate AI systems, we intentionally designed AutoSage-TCM to be totally transparent, making each step of the reasoning process accessible to users. At all times, users remain in control of how to implement the automated analyses and conclusions. AI should be our servants, not our masters.


Neither CCM pathophysiology theory nor the 10-dimensional model of health and illness presented in this lecture are dependent on any theories of scientific materialism. Instead, their validity depends solely on the following criteria:

  • Do they provide us with a way to summarize the directly perceivable reality of symptoms and clinical signs that is consistent with human experience and intuition?
  • Do the resulting analyses of clinical cases consistently lead to successful strategies and remedies that relieve patients' symptoms and, ideally, resolve underlying imbalances on a long-term basis?

The philosophy of scientific materialism has undoubtedly led to much progress and many useful inventions. However, when the scientific method becomes persistently contaminated by political motivations, domination by corporate influence, and intellectual dishonesty, the end result is frequently disastrous. In the 5th and final lecture of this series, I discuss how the recent COVID scamdemic and its associated injectable bioweapons have resulted in rampant worldwide violations of the Nuremberg Code — all made possible by the weaponization of science and the mass deployment of scientific-sounding propaganda wielded by "experts" and authority figures.

Should medical researchers revert to a more traditional era in which physicians had no option but to rely on their own sense perceptions and patients' reports of symptoms — at the very least, as a means of independently checking the potentially flawed or fraudulent theories of scientific materialism? If a medical technique or any health product, for that matter, claims to improve health for specific conditions, clinical studies of CCM analyses for experimental subjects should reveal a systematic improvement in the pattern fingerprint throughout 10-D pattern-space, consistent with claimed improvements in biochemical profile and other lab tests. Likewise, any contraindications or side effects should be characterizable as specific types of CCM fingerprint deviations.


    >> Reference 4-zMedical research error and fraud


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