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HOW ARTIFICIAL INTELLIGENCE IS POISED TO RESHAPE MEDICINE
In a recent review published in the journal of Nature Medicine, scientists discuss the results of a two-year
weekly effort to track and communicate significant developments in medical AI (Artificial Intelligence).
They include prospective studies as well as developments in medical image analysis that have narrowed
the gap between research and implementation. They also discuss non-image data sources, innovative issue
[5] formulations, and human-AI collaboration as prospective pathways for novel medical AI research.
Many randomized controlled trials (RCTs) have been used to assess the utility of AI systems in healthcare.
An RCT evaluating an AI system for managing insulin doses, for example, measured the time patients spent
within the target glucose range, and a study evaluating a monitoring system for intraoperative hypotension
tracked the average duration of hypotension episodes.
[10] AI has also made significant progress in pathology, mainly through the use of whole-slide imaging, in
identifying tumors and offering new disease insights. For example, in gastroenterology, deep learning
has made considerable progress, particularly in terms of enhancing colonoscopy, a vital test for detecting
colorectal cancer.
Despite the remarkable progress in AI, a few obstacles are associated with its widespread use. Although it is
[15] thought that AI will lower medical expenditures, the instruments required to gather data for AI systems can
be prohibitively expensive. Large image sizes raise additional difficulties as the amount of memory needed
for a neural network grows in tandem with the model’s complexity and the number of pixels in the input.
Adapted from: https://www.news-medical.net/news/20220124/How-artificial-intelligence-is-poised-to-reshape-medicine.aspx. Accessed April 10 2023.
Considering the use of AI in medicine, the last paragraph introduces a counterpoint to what is described in the previous paragraphs by mentioning its:
