Medical Pathologies Prediction : Systematic Review and Proposed Approach
This work addresses the problem of optimizing medical processes and patient management for healthcare professionals and patients, but it is incremental as it builds on existing research without introducing a new method.
The authors conducted a systematic review of recent technologies like AI and machine learning in healthcare to propose a general approach for predicting frequent medical pathologies with improved precision and reduced timeframe.
The healthcare sector is an important pillar of every community, numerous research studies have been carried out in this context to optimize medical processes and improve care quality and facilitate patient management. In this article we have analyzed and examined different works concerning the exploitation of the most recent technologies such as big data, artificial intelligence, machine learning, and deep learning for the improvement of health care, which enabled us to propose our general approach concentrating on the collection, preprocessing and clustering of medical data to facilitate access, after analysis, to the patients and health professionals to predict the most frequent pathologies with better precision within a notable timeframe. keywords: Healthcare, big data, artificial intelligence, automatic language processing, data mining, predictive models.