Affiliated project AI4CARDIO
Affiliated CEA : Université Gaston Berger / MITIC & Université d'Abomey-Calavi / SMIA
Title: Conception d'un Système d'Information Médical Intelligent: modèles IA de détection et de prise en charge précoces des maladies cardio-vasculaires au Sénégal.
Niang, F.L., Houndji, V.R., Lô, M., Degila, J., Ba, M.L. (2023) "Use of Artificial Intelligence in Cardiology: Where Are We in Africa? In: Saeed, R.A., Bakari, A.D., Sheikh, Y.H. (eds) Towards new e-Infrastructure and e-Services for Developing Countries. AFRICOMM 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 499. Springer, Cham. https://doi.org/10.1007/978-3-031-34896-9_29
Start date: 01/04/2021
Many healthcare structures in Africa continue to operate manually (e.g. with registers) and to analyze the massive quantities of data (text, images, blood data, etc.) that patients generate during daily consultations, hospitalizations, blood tests, X-rays, births, deaths, etc. .
The manual handling and analysis of these gigantic quantities of data is often the source of errors in the process, which can lead to consequences such as death. The use of paper, or the absence of an information system, wastes an enormous amount of practitioners' time in their day-to-day work.
The aim of this thesis is to design a digital system based on artificial intelligence that will provide doctors with a tool for managing their patients, as well as an intelligent tool for detecting and predicting the risk of cardiovascular disease on the basis of new data.
Objectives / Expected results :
In this thesis project, we aim to develop an AI-based Medical Information System (MIS) capable of:
- Facilitate data analysis and knowledge extraction.
- Assist the medical team in the decision-making process.
- Enable monitoring of patients present and far away.
Contribution / added value to the affiliated project :
Within the framework of this research project, our contribution will be, firstly, a patient management system to be used by doctors during consultations and, secondly, this thesis will lead to the implementation of a system based on artificial intelligence enabling the prediction and early management of cardiovascular diseases in Senegal.
Thesis director :
Prof. Moussa LO, ACE MITIC, Senegal
Thesis co-supervisor :
Prof. Jules DEGILA, ACE SMIA, Benin
Other contributors to thesis supervision :
Dr. Mouhamadou Lamine BA, Université Alioune Diop de Bambey, Senegal