ChatGPT is only so-so at letting physicians know if any given clinical study is relevant to their patient rosters and, as such, deserving of a full, time-consuming read. On the other hand ...
Imperfect algorithms. Resistant clinicians. Wary patients. Divisive disparities. The plot ingredients of a flashy techno-thriller coming to a cineplex near you? No—just a few of the many worries that provider organizations take on when they move to adopt AI at scale.
Higher research and development costs are driving a need for pharmaceutical companies to leverage AI to optimize the drug discovery process––and some companies are doing so better than others.
As an academic AI expert, Pascale Fung, PhD, dove into the scientific research when she was diagnosed with breast cancer in 2015. The time investment rewarded her with a depth of understanding that has helped shape her life as a cancer survivor.
Researchers have found that spiking neural networks become unstable after unbroken periods of unsupervised self-training. Moreover, these “artificial brains” seem to restabilize after they’re given the equivalent of a good night’s rest.
A new scientific statement from the American Heart Association explores the many ways AI and machine learning are being used to improve care for heart patients.