Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Researchers developed a multimodal MRI-based deep learning model to non-invasively identify germinomas among pineal region tumors before surgery. Using 114 pathologically confirmed cases divided into training and test sets, a CNN with contrastive learning and a mixed-attention fusion of MRI sequences and demographic data was evaluated against single-modality models.
On 2026-08-17, a review in Graefe's Archive summarized automated diabetic retinopathy detection and classification using fundus images, surveying ML, DL and hybrid methods, their datasets, pre-processing and metrics, and noting newer ensemble, transformer and attention approaches.
Researchers tested an AI-powered virtual patient application built on ChatGPT to teach Mental Status Examination skills to 27 psychiatric nursing internship students. Using a sequential explanatory mixed-methods design, they measured competency before and after the structured prompting intervention and then interviewed 18 students about their experience.
Researchers developed a hybrid quantum-classical machine learning approach that pairs variational quantum circuits with the ESM2 protein language model in a prototypical network to predict binding partners of Intrinsically Disordered Regions across multiple classes including proteins, nucleic acids, lipids, and metal ions.
Published March 24 2025 in the BMJ, this methods article describes PROBAST+AI, an updated assessment tool for prediction models built with regression or artificial intelligence methods. It splits assessment into model development and model evaluation, each organized around participants and data sources, predictors, outcome, and analysis domains.
Published 25 April 2025, this peer-reviewed case study examines Roblox as a child-focused Metaverse platform, analyzing why automated and human moderation struggles with real-time interactions and massive volumes of user-generated content and documenting failures that left young users exposed to inappropriate content and predatory risks.
Published April 2, 2025 in Nature Communications, this Perspective examines how machine learning is being integrated into decentralized point-of-care testing platforms, including lateral flow, vertical flow, nucleic acid amplification, and imaging-based sensors, following a pandemic-driven shift away from centralized labs.
This review describes the rapid development of large language models such as GPT-4 and their growing use in medicine. By May 2025, the authors state that LLMs have been gradually implemented in clinical practice, medical research, and medical education, while still facing challenges of hallucination, interpretability, and ethics.
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