Clinical Diagnostics

NHS RSET real-world evaluation of AI in chest X-rays: faster prioritisation, positive staff and patient views, cost-effectiveness, but implementation and data gaps.

Google’s AMIE study shows conversational diagnostic AI gathers histories, matches clinician-level top diagnoses, raises patient trust, and operates safely with physician oversight.

PanMETAI combines AI and NMR metabolomics via liquid biopsy to detect pancreatic cancer earlier. Cross-ethnic validation in Taiwan and Lithuania shows strong diagnostic promise.

BrainADNet uses resting-state brain signals and graph convolutional networks to improve Major Depressive Disorder diagnosis and reveal sex-specific neural patterns.

How AI is changing diagnostics: benefits in radiology and pathology, risks like bias and automation bias, and practical steps for safe, clinician-centered adoption.

New AI-driven CSF liquid biopsy reads DNA methylation with M-PACT to identify brain tumors noninvasively. High accuracy, strong potential for pediatric care.

DeepRare, developed at Shenhua Hospital, raises rare disease diagnostic accuracy to 57% with clinical data and over 70% with genetics, offering traceable AI reasoning for clinicians worldwide.

DeepRare, developed by Shanghai Jiao Tong University and Xinhua Hospital, uses an agentic AI workflow to shorten rare disease diagnosis — outperforming Exomiser in Recall@1.

A concise assessment of AI for pulmonary embolism detection: reported accuracy in studies, why performance drops across hospitals, and steps for safer deployment.

Discover how the Health + AI Tech Show in London focuses on real-world AI adoption across clinical AI, genomics, drug discovery and hospital operations. Free registration for NHS staff and clinicians.