HEALTH STATE ESTIMATION USING MACHINE LEARNING
A system and method for health state estimation. In some embodiments, the method includes receiving a first measurement of a subject, the first measurement being a first tissue spectrum of the subject; and generating, using a machine learning inference process based on the first measurement, an estimate of an aspect of the health state of the subject.
1 . A method, comprising:
receiving a first measurement of a subject;
receiving a second measurement of the subject, obtained after the first measurement; and
generating, using a machine learning inference process based on the first measurement and on the second measurement, an estimate of an aspect of the health state of the subject.
2 . The method of claim 1 , wherein the aspect of the health state of the subject is a concentration of a chemical constituent of a tissue of the subject.
3 . The method of claim 2 , wherein the chemical constituent is a substance selected from the group consisting of glucose, cortisol, cholesterol, lactate, ethanol, and water.
4 . (canceled)
5 . The method of claim 1 , wherein:
the first measurement is a first tissue spectrum of the subject, and
the second measurement is a second tissue spectrum of the subject.
6 . The method of claim 5 , further comprising receiving a third measurement of the subject, wherein the machine learning inference process is further based on the third measurement.
7 . The method of claim 6 , wherein:
the third measurement is a third tissue spectrum of the subject, and
the first tissue spectrum and the third tissue spectrum are obtained at different locations on the body of the subject.
8 . (canceled)
9 . (canceled)
10 . The method of claim 1 , further comprising performing a machine learning training process to generate a trained state, wherein
the machine learning training process is based on a plurality of measurements of one or more training subjects; and
the machine learning inference process is further based on the trained state.
11 . (canceled)
12 . The method of claim 10 , wherein the machine learning training process comprises clustering.
13 . The method of claim 10 , wherein the machine learning training process comprises dimensionality reduction.
14 . (canceled)
15 . (canceled)
16 . A method, comprising:
receiving a first measurement of a subject, the first measurement being a first tissue spectrum of the subject; and
generating, using a machine learning inference process based on the first measurement, an estimate of an aspect of the health state of the subject.
17 - 20 . (canceled)
21 . The method of claim 16 , further comprising receiving a second measurement of the subject, wherein the machine learning inference process is further based on the second measurement.
22 . The method of claim 21 , wherein the second measurement is a second tissue spectrum of the subject.
23 . The method of claim 22 , wherein the first tissue spectrum and the second tissue spectrum are obtained at different points in time.
24 . The method of claim 22 , wherein the first tissue spectrum and the second tissue spectrum are obtained at different locations on the body of the subject.
25 . The method of claim 21 , wherein the second measurement of the subject is a result of a chemical analysis of a sample from the subject.
26 . The method of claim 21 , wherein the second measurement of the subject is an image of a portion of the subject.
27 - 31 . (canceled)
32 . A system, comprising:
a processing circuit, the processing circuit being configured to:
receive a first measurement of a subject, the first measurement being a first tissue spectrum of the subject; and
generate, using a machine learning inference process based on the first measurement, an estimate of an aspect of the health state of the subject.
33 . The system of claim 32 , wherein the aspect of the health state of the subject is a concentration of a chemical constituent of a tissue of the subject.
34 . (canceled)
35 . The system of claim 32 , wherein:
the processing circuit is further configured to receive a second measurement of a subject, the second measurement being a second tissue spectrum of the subject, obtained later than the first measurement; and
the generating of the estimate of the aspect of the health state of the subject comprises using a machine learning inference process further based on the second measurement.
36 . The system of claim 32 , further comprising a portable spectrophotometer, configured to obtain a plurality of tissue spectra including the first tissue spectrum.
37 . (canceled)