Beginnings of Artificial Intelligence in Medicine (AIM): Computational Artifice Assisting Scientific Inquiry and Clinical Art - with Reflections on Present AIM Challenges.

BACKGROUND: The rise of biomedical expert heuristic knowledge-based approaches for computational modeling and problem solving, for scientific inquiry and medical decision-making, and for consultation in the 1970's led to a major change in the paradigm that affected all of artificial intelligence (AI) research. Since then, AI has evolved, surviving several "winters", as it has oscillated between relying on expensive and hard-to-validate knowledge-based approaches, and the alternative of using machine learning methods for inferring classification rules from labelled datasets. In the past couple of decades, we are seeing a gradual but progressive intertwining of the two.