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How can AI accelerate advances in physiology?

Biology

How can AI accelerate advances in physiology?

A. D. Mcculloch

Discover how artificial intelligence is set to revolutionize physiology in this insightful research by Andrew D McCulloch. This study delves into the challenges of data overload in biology and highlights the potential of deep learning to connect genetic data with tissue function, particularly in cardiac myocytes.

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Playback language: English
Abstract
This paper explores the potential of artificial intelligence (AI) to accelerate advancements in physiology. It argues that while biologists often face data overload, physiologists struggle to connect genotype and structure to tissue and organ function. AI, particularly deep learning, offers potential shortcuts for predicting pathophysiological phenotypes from molecular data. However, the paper cautions that these approaches require substantial training data and may lack mechanistic explanations. A promising strategy involves using well-validated, mechanistic computational models to discover genotype-phenotype relationships and generate new hypotheses. The study focuses on cardiac myocytes and the use of machine learning to analyze isometric twitch tension, identifying features that classify disease mutations with high accuracy.
Publisher
Journal of General Physiology
Published On
Jan 01, 2023
Authors
Andrew D McCulloch
Tags
artificial intelligence
deep learning
physiology
genotype-phenotype relationships
cardiac myocytes
machine learning
pathophysiological phenotypes
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