ASSESSING DISEASE RISKS FROM USER CAPTURED DATA

In some examples, an apparatus (100), such as a mobile phone can include an input module (102) such as a touch screen, a camera (104), a processor, and computer readable medium. The camera (104) captures one or more images of a person. The processor can use a single machine learning model (110) to e...

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Bibliographic Details
Main Authors EL-SALLAM, Amar, BOSANAC, Vlado
Format Patent
LanguageEnglish
Published 17.08.2023
Subjects
CALCULATING
COMPUTING
COUNTING
DIAGNOSIS
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Summary:In some examples, an apparatus (100), such as a mobile phone can include an input module (102) such as a touch screen, a camera (104), a processor, and computer readable medium. The camera (104) captures one or more images of a person. The processor can use a single machine learning model (110) to estimate the human body features of the person based on the captured images, and use the human body features to generate a disease risk assessment value associated with diabetes and cardiovascular disease risks. The human body features can include at least one or more of: 3D body shape, or body shape indicators; and one or more of: blood flow, blood pressure, heart rate, respiratory rate, heart rate variability, cardiac workload, irregular heartbeats, or stress index. The machine learning model (110) can be trained over a set of training images.
Bibliography:Application Number: AU20220236936