Sep 2026· Australian Journal of General Practice· Vol 55 9, pp.
648-651
· 0 citations
Medicine
TL;DR
The aim of this article is to give a non-technical overview of AI and its medical applications, with particular emphasis on large language models.
Abstract
Background
Artificial intelligence (AI) is thought by many to likely underpin the next revolution in clinical medicine. The rapidly evolving terminology in AI - including terms such as 'generative AI', 'machine learning' and 'natural language processing' - can present a barrier to clinical adoption.
Objective
The aim of this article is to give a non-technical overview of AI and its medical applications, with particular emphasis on large language models.
Discussion
The term 'AI' suggests semantic understanding. This impression is reinforced by text output eerily similar to human writing. However, AI has not yet become intelligent in the common understanding of that word. The apparent semantic understanding is not actually there. Knowing this is crucial to avoiding misapplications of this nevertheless revolutionary technology.
Simple Summary This paper looks at whether artificial intelligence (AI) can help doctors detect and manage blood clots in cancer patients—a serious condition called cancer-associated thromboembolism (CAT). The authors explain that while AI shows promise for finding clots on CT scans, it often gives false alarms, especi...
Julia H. Miao, Ola A. E. Mohamed, Christopher Straus et al.· Cancers· 0 citations
The advent of artificial intelligence (AI) in healthcare operations is both promising and perilous. This paper reflects on the importance of experience, defined as our on-going, direct interactions with the world that enhance our abilities and establish useful habits, and then discusses potential implications of AI as...
Daniel T. Nystrom, Russell Leslie, Jonathan G. Sawicki· Proceedings of the Internati...· 0 citations
Artificial intelligence (AI) systems that model human behaviour are built on data humans generate about themselves, yet the assumption that this data is reliable remains largely unexamined. Psychiatry's evidence base directly challenges it. Self-report is shaped by cognitive distortions, the gap between clinical presen...
By explaining what is 'deep' about deep learning and showing that AI is more maths than magic, the briefing aims to equip the reader with the understanding they need to engage in clear-headed reflection about AI's opportunities and challenges.
Bedside use of artificial intelligence (AI) platforms is increasingly common. Busy clinicians may welcome these generative AI (Gen AI) tools, which have the potential to streamline many time-consuming tasks and aid in patient care. Trainees may find them useful to quickly evaluate complex medical information. Acceptanc...
K. MacDuffie, Douglas S. Diekema, J. Kett et al.· Pediatrics· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.