From Mind-Reading to Health-Reading Machines: Towards Contactless Health Diagnosis using Generative Artificial Intelligence

Abstract

Generative Artificial Intelligence (AI) has recently shown impressive results across a wide spectrum of tasks. Inspired by the emerging notion of mind-reading machines and by the medical evidences indicating that some diseases and brain disorders produce facial abnormalities and interrupt normal facial expression formation, we are (1) establishing, in close interaction with medical practitioners, the basic understanding of the correlations between visual patterns and health conditions, and (2) developing novel computational models, based on Generative AI, to learn the identified correlations. Devising computational models for detecting abnormalities reflective of internal diseases based only on visual information is a highly intriguing research problem. The goal is to achieve ground-breaking results in unobtrusive health diagnosis and to gain insight into the correlation between face, body, and mind. This work has the potential to open new research directions in several fields and to bridge the gap between the research activities conducted in several disciplines like engineering and medicine. This article explains the main idea behind contactless health reading using generative artificial intelligence.