Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
On 2026-08-26, a peer-reviewed study described TrialScout, a program that uses a large language model to link ClinicalTrials.gov registrations to PubMed result publications. Tested against prior human-coded datasets, it achieved 92.5% sensitivity and 81.2% specificity, and when applied to 9,600 sampled completed or terminated trials it identified publications for 6,110 trials.
Researchers developed EDLF-SLC, an explainable deep learning framework for skin lesion classification that fuses features from multiple pretrained CNNs, classifies them with an RBF-kernel SVM, and explains predictions with LIME. In experiments reported in August 2026, the system reached 88% accuracy and 88% F1, presented as competitive with recent methods.
Researchers developed three adaptive ensemble voting methods that assign weights based on per-class F1-scores from validation instead of overall accuracy. They tested the approaches on Gaussian Mixture, Spiral, and Moon synthetic datasets and on the Breast Cancer Wisconsin and UCI Heart Disease datasets, comparing against majority, weighted, and soft voting.
Researchers collected paired samples from 94 right-handed participants who each wrote the same standardized text with dominant and non-dominant hands, then scored 13 general and 19 individual characteristics. They found statistically significant differences in 61.5% of general and 57.9% of individual characteristics and trained a supervised logistic regression model to distinguish hand use.
By March 2026, this peer-reviewed overview described how AI-based automation in Industry 4.0 optimized production, logistics, and resource management to reduce waste and energy use, and how Industry 5.0 expanded that with human-machine collaboration, generative AI, digital twins, and decentralized smart grids and microgrids.
In a July 2026 peer-reviewed study, 57 first-year medical students completed 24 paired clinical and foundational questions during a pediatric nephrology and urology case-based session, answering individually, then viewing a ChatGPT-generated answer that was deliberately correct or incorrect, and re-answering.
A scoping review published May 25, 2026 examined 270 peer-reviewed studies from 2002 to 2024 on machine learning in sport. It found applications across 12 subject areas, most frequently computer science, biomechanics, and sport psychology, with common uses in action recognition, injury prediction/prevention, and athlete selection/talent identification.
In a structured stress test published February 23, 2026, researchers evaluated ChatGPT Health, OpenAI's consumer health tool launched in January 2026, using 60 clinician-authored vignettes across 21 clinical domains under 16 factorial conditions to generate 960 responses, assessing triage recommendations and contextual sensitivity.
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