Menu
Back to AI and Diagnosis
08/25/26

Can artificial intelligence really help? A practicing radiologist’s simplified guide to AI, with a critical appraisal of the use of AI in cancer-associated thromboembolism.

Miao, Julia H; Mohamed, Ola A E; Straus, Christopher; Peters, Vanessa; Miller, Emily; Dawoud, Basant; Brooks, Joshua; Megahed, Haidy; Hamimi, Ahmed. Cancers.

Collection Topics
AI and Diagnosis Big Three Conditions Tests, Screening, and Laboratory Processes
Share

Most recent

On-premise medical AI agents for reliable clinical decision-making.

Zhang, Wölflein, Ferber, et al., Nature Med.
09/15/26 AI and Diagnosis

Heuristic or algorithmic thinking? Assessing generative AI’s impact on human decision-making. A literature review.

Fernández-Concha, Solórzano Muñante, Appl Artif Intel.
09/15/26 AI and Diagnosis Cognition and Decision Making

Scaling clinical judgment to evaluate medical AI.

Buckley, Kanjee, Brodeur, et al., arXiv
09/11/26 AI and Diagnosis Measurement, Monitoring, and Event Analysis

Summary

The diagnostic protential of AI can exceed the evidence supporting its clinical use. This narrative review provides a practical overview of AI in radiology before critically examining applications to cancer-associated thromboembolism. It discusses incidental detection, risk stratification, and treatment support while highlighting the limitations of AI such as data heterogeneity, limited prospective validation, generalizability problems, and workflow challenges.
Read the paper
Miao JH, Mohamed OAE, Straus C, et al. Can artificial intelligence really help? A practicing radiologist’s simplified guide to AI, with a critical appraisal of the use of AI in cancer-associated thromboembolism. Cancers (Basel). 2026;18(17):2753.