The Role and Promise of Artificial Intelligence in Medical Toxicology.

Publication Type	Review
Authors	Chary M, Manini A, Boyer E, Burns M
Journal	J Med Toxicol
Volume	16
Issue	4
Pagination	458-464
Date Published	03/25/2020
ISSN	1937-6995
Keywords	Artificial Intelligence, Big Data, Data Mining, Psychotropic Drugs, Toxicology
Abstract	Artificial intelligence (AI) refers to machines or software that process information and interact with the world as understanding beings. Examples of AI in medicine include the automated reading of chest X-rays and the detection of heart dysrhythmias from wearables. A key promise of AI is its potential to apply logical reasoning at the scale of data too vast for the human mind to comprehend. This scaling up of logical reasoning may allow clinicians to bring the entire breadth of current medical knowledge to bear on each patient in real time. It may also unearth otherwise unreachable knowledge in the attempt to integrate knowledge and research across disciplines. In this review, we discuss two complementary aspects of artificial intelligence: deep learning and knowledge representation. Deep learning recognizes and predicts patterns. Knowledge representation structures and interprets those patterns or predictions. We frame this review around how deep learning and knowledge representation might expand the reach of Poison Control Centers and enhance syndromic surveillance from social media.
DOI	10.1007/s13181-020-00769-5
PubMed ID	32215849
PubMed Central ID	PMC7554271