Abstract: A machine learning model for stratification of early diabetic foot complication using thermogram images is provided that is operable to predictively diagnose a risk for diabetic foot ulceration formation via receiving a thermogram of a foot; identifying, via a machine learning model, a risk factor of diabetic foot ulceration on the foot; and outputting, from the machine learning model, the risk factor as a diagnosis.

Abstract: An apparatus for communicating health care data from a sender to a receiver is provided. The apparatus has a first computer system, a second computer system, and a rules engine. The first computer system has health care data stored therein. The second computer system is in operable communication with, and is configured to extract the health care data from, the first computer system. The rules engine normalizes the extracted health care data to a predefined format.

Abstract: An apparatus for communicating health care data from a sender to a receiver is provided. The apparatus has a first computer system, a second computer system, and a rules engine. The first computer system has health care data stored therein. The second computer system is in operable communication with, and is configured to extract the health care data from, the first computer system. The rules engine normalizes the extracted health care data to a predefined format.

Abstract: An apparatus for communicating health care data from a sender to a receiver is provided. The apparatus has a first computer system, a second computer system, and a rules engine. The first computer system has health care data stored therein. The second computer system is in operable communication with, and is configured to extract the health care data from, the first computer system. The rules engine normalizes the extracted health care data to a predefined format.

Abstract: An apparatus for communicating health care data from a sender to a receiver is provided. The apparatus has a first computer system, a second computer system, and a rules engine. The first computer system has health care data stored therein. The second computer system is in operable communication with, and is configured to extract the health care data from, the first computer system. The rules engine normalizes the extracted health care data to a predefined format. The rules engine defines a plurality of health care data fields in the predefined format, as well as a plurality of relationships between fields of normalized data.

Abstract: A system and method for generating and/or updating a personal/individual health record. Inputs of data to the system may come from diverse sources including, but not limited to, patient questionnaires, insurance company (or other payor) claims data, hospitals, clinics and other institutional providers, and individual physicians and physicians' offices.

Abstract: A system and method for generating and/or updating a personal/individual health record. Inputs of data to the system may come from diverse sources including, but not limited to, patient questionnaires, insurance company (or other payor) claims data, hospitals, clinics and other institutional providers, and individual physicians and physicians' offices.

Abstract: A system and method for generating and/or updating a personal/individual health record. Inputs of data to the system may come from diverse sources including, but not limited to, patient questionnaires, insurance company (or other payor) claims data, hospitals, clinics and other institutional providers, and individual physicians and physicians' offices.

Abstract: A system and method for generating and/or updating a personal/individual health record. Inputs of data to the system may come from diverse sources including, but not limited to, patient questionnaires, insurance company (or other payor) claims data, hospitals, clinics and other institutional providers, and individual physicians and physicians' offices.

Abstract: A system and method for generating and/or updating a personal/individual health record. Inputs of data to the system may come from diverse sources including, but not limited to, patient questionnaires, insurance company (or other payor) claims data, hospitals, clinics and other institutional providers, and individual physicians and physicians' offices.