Method for Enhanced Medical Data Pattern Recognition

Abstract

The present invention provides a method for enhanced medical diagnostic data pattern recognition in an individual or in a population of individuals. The method comprises compiling a dataset consisting of at least seven essential vital signs of an individual or population of individuals, wherein the dataset is compiled and mapped in at least three ways: (1) as a mathematical tensor; (2) as a visual graph; or (3) as a musical composition. Essential vital signs can include systolic pressure values of 60-140; diastolic pressure values of 40-85; time of day values of 1-24; oximeter data values of 92-99; date data values translated to adjusted circadian process; pulse data values of 40-90; and weight values.

Claims

1. A method for medical diagnosis comprising the steps of: electing at least seven vital signs or indicators of an animal or human for which diagnosis is indicated; monitoring said vital signs or indicators over time with data capture; and compiling and mapping said data, using a computer, to map said data capture in a form selected from the group consisting of a mathematical tensor, a visual graph and a musical composition.

2. The method according to claim 1, wherein said form further comprises (1) a linear graph of x, y, z, as x=t{circumflex over ()}y=P/p; x=t{circumflex over ()}y=pBpm{circumflex over ()}z=dP; (2) a hyperbolic graph; (3) a symbolic logic graph; or (4) a logarithmic graph.

3. The method according to claim 1, wherein said compiling and mapping are calculated according to the equation: x= 7+y (v.sub.n1, n2, n3, n4, 5, n6, n7 . . . ), wherein x is the output to a user; y=0-100; and n=individual vital sign or indicator data or time.

4. The method according to claim 1, wherein said compiling and mapping are calculated according to homologic equations: If l is a face of a simplex kK, then lK. For k, lK, klkkll.

5. The method according to claim 3, wherein n is selected from the group consisting of systolic pressure, diastolic pressure, body temperature, time elapse, oximeter, pulse, body mass, antibody titer, white cell count, T cell count, red cell count, a cancer marker, hematocrit, hemoglobin, platelet count, platelet volume, an immune marker, a metabolic marker, and an indicator.

6. The method according to claim 5, wherein said indicator is a marker.

7. The method according to claim 1, wherein said at least seven vital signs include (1) systolic pressure values of 60-140; (2) diastolic pressure values of 40-85; (3) time of day values of 1-24; (4) oximeter data values of 92-99; (5) date data values translated to adjusted circadian process; (6) pulse data values of 40-90; and (7) weight values.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0014] The present invention provides a method comprising compiling a dataset consisting of at least seven essential vital signs of an individual, wherein the individual dataset is compiled and mapped in at least three ways: (1) as a mathematical tensor; (2) as a visual graph; or (3) as a musical composition.

[0015] Such a dataset, being a unique array, constitutes a description of an individual, and being so personalized, the dataset is a unique tensor equivalent to an individual fingerprint, and is infinitely more unique than genetic analysis of the individual.

[0016] The present invention therefore takes medical vital signs or indicators and renders them in a compiled form, for instant or prompt viewing or auditory review. The ways a computer can compile such data capture are endlessthe invention is both in knowing to render such data capture in this new way, and in programming the computer to do it, such that the output to a user is reviewable by sight or sound and patterns therein are recognizable as having meaning.

[0017] With respect to compiling and mapping an individual's dataset as a mathematical tensor, it can be represented as a straightforward Einsteinian Tensorial Array, i.e., a multi-dimensional array of numbers.

[0018] With respect to compiling and mapping an individual's dataset as a visual graph, it can be either: (1) a linear graph, i.e., x, y, or x, y, z, e.g., x=t{circumflex over ()}y=P/p; x=t{circumflex over ()}y=pBpm{circumflex over ()}z=dP; (2) a hyperbolic graph; (3) a symbolic logic graph; or (4) a logarithmic graph.

[0019] With respect to compiling and mapping an individual's dataset as a musical composition, each parameter can be mapped to a set-inclusive range which defines, for example and without limitation:

[0020] 1. Systolic pressure values of 60-140, which can be mapped 1-9, e.g., melody notes Middle C to c;

[0021] 2. Diastolic pressure values of 40-85, which can be mapped 1-12, e.g., chromatic melody notes;

[0022] 3. Time of day values of 1-24, which can be mapped to two octaves of bass notes;

[0023] 4. Oximeter data values of 92-99, which can be mapped to 1-8 continuo definition;

[0024] 5. Date data values translated to adjusted circadian process, which can be mapped to 2/4, , 4/4, 6/8, , etc., rhythm patterns;

[0025] 6. Pulse data values of 40-90, which can be mapped to 1-6 pianissimo to pffForte; and

[0026] 7. Weight values, being hard to collect, can be mapped to Key Signatures.

[0027] The gravamen of the present invention is the mathematical conversion of patient data into a gestalt, in a way that no diagnostic reporting has ever done before. The gestalt, or big picture, is typically a kind of heads up display, in which a physician or other health care provider can see complicated data reduced to any or all of a mathematical tensor, a visual graph or even a musical composition that can be heard, instead of viewed. The importance of this approach is, in part, that individual vital signs or indicators have additive significance, beyond just being within or out of normal range themselves, particularly when change in sign or indicator are considered together and over time.

[0028] In other words, it is good to know whether two (or more) signs or indicators are within or outside of their normal rangesbut how does the diagnostician readily discern when both those signs or indicators, together, are significant in their variations, both in concert and as they change over time?

[0029] Those skilled in the art will immediately appreciate the utility of the described and claimed invention. An early iteration of a parallel idea, not suggestive of the present invention, was also immediately apparent to those skilled in the artU.S. Pat. No. 6,063,586 to Jennifer Grandis, entitled Diagnostic Protocol. In this patent, static graphing of data in two dimensions only, of EGFR and TGF levels, proved diagnostically significant of specified patient outcomes when data clustered in a particular quadrant of the two-dimensional graph (see, for example, FIG. 4). Nothing in U.S. Pat. No. 6,063,586 suggests, however, anything like the present invention, which multiplies the number of signs or indicators to at least seven, typically and ideally includes time as a variable, and importantly renders the compiled data as a visual or auditory output reducing multiple dimensions to a display that can be comprehended all at once.

[0030] The mathematics of compiling data sets according to the present invention is within the skill of the art, but has to the inventor's knowledge never been deployed in the method as presently claimed. For example, in Johnson, C. A., Applications of Computational Homology, Marshall Digital Scholar, Marshall University, Jan. 1, 2006, the author reviews manipulation of complex homological surfaces such as can, without limitation, be generated with the present invention. In compiling the present data capture when the data compilation will naturally create a homological surface representing multiple dimensions (data), an n-dimensional simplicial complex K constitutes a collection of simplices of dimensionn, where n is 100, such that:

If l is a face of a simplex kK, then lK.
For k, lK, klkkll.

[0031] However, when homological surfaces do not need to be taken into account, such as for mapping of multiple variables over time as, for example, musical aggregations, the following equation is used to implement the automated computation of data compiling and mapping:

x= 7+y (v.sub.n1, n2, n3, n4, n5, n6, n7 . . . ), where x is the output resulting from the compiled and mapped data capture (solved for by the equation);
y=0-100; and
n=patient (or animal) vital sign or indicator with n1, n2, n3 . . . representing individual vital signs or indicator variables including, optionally, time.

[0032] In the context of the previous equation, means either summation or aggregation.

[0033] When implementing automated data compiling and mapping with either, or both, of the above equations, the patient (vital) signs or indicators, compiled and mapped, may be between 7 and 100. While the compiling and mapping is automated, the selection of 7-100 signs or indicators is discretionary on the part of the physician or health care providerand the invention operatesto render gestalt dataregardless of which signs or indicators are selected.

[0034] The present invention, thus allowing an accumulated, compiled and tensorialized Manifold Medical Data-Set to be displayed mathematically, visually, sonically or musically, enjoys utility and is medically valuable because it allows for mathematical, visual, sonic, or musical recognition of patterns otherwise undiscerned. The present invention, therefore, is useful to a medical diagnostician in developing a therapeutic analysis leading to highly individualized treatment protocol(s). In addition, the present invention provides a novel and heretofore unknown method of programmatic and axiomatic musical composition in the style of Tone Rows of musical composers.

[0035] Further, the present invention has applicability not only to pattern recognition for data sets, generally of multiple human or animal subjects, but also in the pattern depiction of data-over-time for an individual subject. For example, in the Exemplification shown below, four months of four patient data parameters, stipulated as to date and time, are listed in a table array. For a health care provider, who is used to considering static assessments of blood pressure, oxygenation, weight and so forth, historically it has been difficult to view a time-based array of such data to see where the meaningful fluctuations are. In the case of an individual's signs and symptomsthose skilled in the art already know what patterns to look for over timehow can those signs and symptoms be depicted for easy recognition when a page full of raw data are so hard to read, especially to read quickly and accurately?

[0036] The answer is that an enhanced graph or musical depiction, according to the present invention, makes the data progression pattern quickly discernible to the eye or ear. Consider, for example, as shown in the Exemplification, that there is a cyclical nature to the variance in blood pressure systolic/diastolic values. It certainly is possible for a health care provider to run the eye down the column of values to discern the fluctuation and its significance. It is very much easier, and less likely to produce error, for the health care provider to see the pattern in the data in an enhanced graph, or to hear it as sound/music, to discern the data patterns that are less easy to see in a data array or matrix.

TABLE-US-00001 EXEMPLIFICATION: PATIENT RIOCO J'HANCIOCIOLA (TAMPA BAY, FLORDIA) Sporadic & Select Vitals 2019 Date Time BPsd % SpO.sub.2 PRbPm W . . . January 27 130a 70/40 97 39 205 27 1130a 70/50 93 60 208 . . . February 20 530a 63/47 98 55 205 20 Noon 100/58 98 49 204 21 6a 60/50 98 45 204 22 2p 100/70 99 60 204 . . . March 02 4a 120/70 98 82 204 03 3a 60/48 ? 77 203 03 9a 70/50 97 75 203 03 Noon 80/55 98 60 202 04 10a 90/55 98 60 203 04 2p 70/55 98 57 203 06 9a 80/50 99 70 202 07 4p 75/50 97 67 206 08 6a 75/55 99 65 204 10 11a 75/50 ? 62 207 10 430p 80/55 98 85 206 10 7p 85/50 97 46 205 10 10p 75/40 97 48 204 14 3p 70/50 98 58 206 15 7a 75/50 97 70 203 17 1a 75/45 98 48 202 20 3a 85/60 97 60 207 20 11a 80/60 97 55 205 21 3p 100/60 98 86 208 24 7a 99/64 97 68 208 24 930p 95/60 95 44 205 25-01 Unable to Track . . . . . . April 02 2a 65/55 ? ? 207 03 5a 53/38 97 65 206 09 Noon 99/64 97 55 211 10 10p 65/50 97 70 ?? 15 2p 120/70 99 62 209 16 530a 70/50 97 50 209 16 9p 100/50 98 50 208 17 2p 65/40 97 70 208 18 1030a 125/80 98 50 208 19 1030a 58/43 92 70 207 20 3p 70/45 97 45 207 21 230p 56/36 97 65 206 22 5p 68/40 97 52 205 30 3p 120/80 98 70 202 . . . May 04 1p 100/70 98 70 208 05 12a 95/65 98 70 207 06 1p 85/55 97 55 208 07 1p 100/60 98 60 208 10 11a 120/85 93 89 208 11 11a 100/70 97 80 207 12 1a 100/65 98 100 206 13 5a 110/75 97 80 208 16 11a 90/55 97 45 210 18 9p 75/50 98 52 206 19 130a 90/44 97 50 205 21 5p 65/40 99 85 203 30 9p 70/40 97 55 205

[0037] The value of the enhanced graph or audible patterns does not stop with the diagnostician. A patient can benefit from hearing his or her own data renditionsor seeing the enhanced graphing of themby recognizing certain patterns which then may be a representation of signs or symptoms the individual wishes to change. Considering again the blood pressure example, if a goal is to even out fluctuations in blood pressure, at successive health consultations the individual can listen to the current blood pressure trends or look at them with enhanced graphics. If interventions to smooth out blood pressure variation have been successful, the patient will later see or hear the new pattern and enjoy the positive feedback. Also, no one likes to be nagged, and it is quite different to hear someone cajole Lose weight! Stop smoking! (negative), then it is to see or hear the pleasant visual or tonal adjustments of, say, weight reduction, bad cholesterol improvement, and so forth (positive). Alongside this wellness and biofeedback benefit, the graphic or musical rendition for each patient is an independent fingerprint of patient data each time, and so is unique to the patient.

[0038] Thus, the present invention provides a graphic or music/sound way for a person not only to hear a depiction of their unique identity, but to have an entirely new way of looking in a mirror, for self-assessment or for registry of individuality by others.

[0039] Pattern analogizing between individual patients and patient populations, or among patient populations, is still in development at this writing. The significance of certain patterns in data as to populations will be developed with this inventive technique, which is not an abstraction and does not use any conventional steps. In other words, the present invention as to populations is not a pie-in-the-sky aspiration of finding patterns in clinical study data sets. Instead, the present invention is a way of organizing and displaying datadata already understood to contain its own multiple meanings that can be assessed by means already known in the artin a way that can be more easily characterized, categorized, rendered and archived than data presentation means of the prior art.

[0040] Without question, the present invention improves the efficiency of computers tasked with rendering outputs of data sets, due to the simplification of the data into enhanced graphics or music/sound in ways which reduce computation needed and therefore speeds up processing. Moreover, the ability to depict individual patient data over time already exists, and can literally be generated by, as a nonlimiting example, inputting the data from the Exemplification provided herein into a music program such as GuitarPro, to generate a music/sound file after assigning a music parameter to each data typeor analogously by assigning each data type to a parameter in an enhanced graphing protocol for visual output.

[0041] Overarchingly, therefore, the present invention addresses two separate universes of trends: (1) the dynamic model of single patient data (multiple data types) over a specified time period, for pattern depiction; and (2) the clinical study model of identifying patterns in populations by assessing (multiple) patient data over time the same way. With the individual, there may or may not be an existing diagnosis to which data patterns can be mapped. In populations, there likely will already be a common diagnosis which can, in turn, be mapped to patterns that emerge from the patient population datain enhanced graphing or in music/sound trends.

[0042] While the invention has been particularly shown and described with reference to embodiments described above, it will be understood by those skilled in the art that various alterations in form and detail may be made therein without departing from the spirit and scope of the invention, as defined by the appended claims.