Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
On 2026-08-06, a peer-reviewed study described an integrated assessment for a mountainous area in northern Iran covering flood, avalanche, rockfall and landslide. Authors trained ANN, RF and SVM models on 21 environmental variables and validated them against field inventories, then combined outputs with fuzzy AND, OR and GAMMA operators to distinguish compound from cumulative hazard zones.
A single-arm meta-analysis published August 6, 2026 pooled 30 independent test datasets totaling 67,266 non-contrast CT scans to compare convolutional neural networks, U-Net, and hybrid deep learning models for subdural hematoma detection. U-Net models demonstrated significantly higher sensitivity and precision, while all architectures showed consistently high specificity, diagnostic odds ratio, and accuracy.
A cross-sectional survey of 454 final-year dental students in the UAE, Jordan, Malaysia, Oman, and Brazil examined LLM use, motivations, and safeguards. Published August 6 2026, it found ChatGPT predominated at 95.9%, with 39.2% using LLMs several times per week and 28.6% daily for tasks like understanding complex concepts and summarising lecture notes.
A systematic review and diagnostic meta-analysis of 20 studies, 14 in quantitative synthesis, evaluated machine learning models to predict clinical pregnancy or live birth after assisted reproductive technology. As of the August 2026 publication, pooled sensitivity was 0.737 and specificity 0.789 with a DOR of 10.49 and acceptable discrimination on SROC, but heterogeneity was very high.
This narrative review from June 2026 synthesized evidence on AI integration in radiology, finding that by that date AI systems had shown diagnostic performance approaching or exceeding radiologists in chest imaging and breast cancer screening and had improved triage and reduced report turnaround times in practice.
A peer-reviewed commentary from April 2026 describes how AI tools are being adopted in the humanitarian cooperation sector to improve health diagnostics, service quality, and efficiency of analysis and data management for emergency responses in conflict areas with limited resources.
Researchers nested a two-part methodological study within two PROSPERO-registered reviews to test customized GPT models on complex rheumatology evidence synthesis. Fifteen SLE metabolomics studies were used to compare human and GPT data extraction, and nineteen rheumatology prognostic studies were reappraised in 2025 with GPT-Reviewer against adjudicated human QUIPS ratings using weighted kappa.
By July 10 2026, a peer-reviewed review in Tissue Engineering Part B: Reviews evaluated experimentally validated AI uses in scaffold-based bone regeneration, from materials design to fabrication control and biological assessment. It reported that physics-informed models tend to be more robust and generalizable than purely data-driven models, while transfer learning is hampered by variability in cellular responses and fabrication conditions.
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