Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
The I3LUNG study enrolled 2,396 patients with non-small cell lung cancer to develop AI models for immunotherapy selection, integrating clinical and blood data, CT, digital pathology and genomics into early and intermediate fusion models. CB-only models reached AUC up to 0.77 in the independent TEST set and outperformed PD-L1, ECOG PS, NLR, LDH and LIPI, and a usability study found physicians improved predictions with the explainable AI tool.
By September 2026, researchers reported a multi-task deep learning model based on 3D-ResNet18 designed to assist expert judgment of rib fracture age from chest CT. Trained on 1,848 fractures from multiple centers, the model was tested externally and reported to predict fracture age, healing stage, and fracture type concurrently.
This narrative review from Chinese Medical Journal examines how AI in laboratory medicine has evolved from conventional machine learning on structured results to deep learning and large language models that handle unstructured clinical text. It compares four paradigms and reviews evidence across blood cell morphology, autoverification, infectious risk stratification, urinalysis interpretation, decision support, and report generation.
A Communications Medicine overview published October 10 2023 examines large language models as text-processing AI tools that gained wide attention after ChatGPT's November 2022 release, assessing their near-human ability to answer, summarize and translate and their emerging use in clinical practice, medical research and medical education.
On 2026-08-16, a peer-reviewed paper in Discover Artificial Intelligence described rising energy use and emissions from growing deep learning workloads in contemporary data centres and presented EcoSchedAI, a carbon-aware job scheduling framework intended to bring carbon awareness into actual machine learning operational processes.
A faculty author describes personalizing a written assignment to reduce students copying and pasting from generative AI outputs, then analyzes 81 paper grades from the course to assess impact.
This peer-reviewed review in GeroScience appraises CT-based prediction of hematoma expansion after spontaneous intracerebral hemorrhage, a major determinant of early deterioration. It compares contrast-enhanced signs like spot, leakage and iodine signs with non-contrast signs including blend, black hole, island, satellite, hypodensity and swirl signs, plus shape and heterogeneity, and evaluates composite scores and AI approaches including radiomics, machine learning and deep learning.
On 2026-08-15 a discursive paper in Journal of Advanced Nursing explored post-humanism and AI in nursing and healthcare through critical reflection on contemporary and established literature. It concluded AI presents both potential benefit and severe threat to fundamental nursing care defined by patient/nurse relationships and patient-centredness carried out with critical reasoning.
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