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Artificial Intelligence for Medical information

Prediction of the risk of developing a complication at an early stage plays a key role in an adequate treatment and follow-up of the diabetic patient.

Diabetes predictionPublications

Our Goal is the Integration in the electronic medical record (EHR) of a clinical decision support system (CDSS) based on Artificial Intelligence (AI) to help the diabetologist.

Our Goal is the Integration in the electronic medical record (EHR) of a clinical decision support system (CDSS) based on Artificial Intelligence (AI) to help the diabetologist.

What is AIMedical?

AIMedical is an algorithm that can be applied to all diabetes complications It is easily exportable to other national and international clinical files.

Clinics Big Data

Big data in diabetes centers (i.e., high number of patients, high number of characteristics per patient, etc.)

Doctors

The doctor is indispensable for entering correct structural data and for correcting incorrect deductions on the AI

Telemedicine

Telemedicine from diabetics will be another source of information to add to that of the folder

Our team

“Delivering the right treatments, at the right time, every time to the right person.”

Barack Obama

Predictive medicine

See our news

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  • A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment

    A Hidden Semi-Markov Model (HSMM) based approach is proposed to evaluate and monitor body motion during a rehabilitation training program.

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  • A sequential deep learning application for recognising human activities in smart homes

    The recent advancement and development of computer electronic devices has led to the adoption of smart home sensing systems, stimulating the demand for associated products and services.

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  • A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation

    Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices.

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Our investors

Medical software and devices for Diabetes and Nutrition.

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Center for Outcomes Research and Clinical Epidemiology.

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Collaborators

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