Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Using GBD 2021 data, Mendelian randomization, and a clinical cohort, the study quantified global PMOS burden and tested adiposity as a causal determinant, then built machine-learning models from body-composition measures to predict PMOS, with XGBoost reaching AUC 0.701 and SHAP highlighting left-leg and trunk fat mass.
This peer-reviewed review examines AI, including machine learning and deep learning, for cardiovascular prevention in Italy and globally, where cardiovascular diseases remain the leading cause of mortality and morbidity. It surveys evidence that AI can deliver more precise, dynamic and personalized risk stratification than traditional scores and support early detection of subclinical disease via AI-enabled electrocardiography and opportunistic imaging.
On September 1, 2026, a peer-reviewed roadmap in Xenotransplantation outlined how artificial intelligence could be integrated into early clinical xenotransplantation to address organ shortage. It prioritizes digital pathology, machine perfusion monitoring, multimodal graft injury detection, and xenozoonotic infection surveillance, emphasizing clinician-supervised, auditable systems combined with gene-edited donors.
On 2025-10-14, a peer-reviewed article in Qualitative Research in Psychology proposed a social science futures research agenda centered on artificial intelligence. The author describes a contemporary market for futures knowledge driven by promises of faster, scaled-up AI foresight, and examines Generative AI as an anticipatory infrastructure through which international organizations imagine futures, participants engage with dominant visions, and researchers imagine future methods.
Published 2026-08-04, this peer-reviewed comparative case study examines passages from George Orwell's Nineteen Eighty-Four and Ross Goodwin's 2018 sensor-driven LSTM book 1 the Road to assess how generative systems handle literary coherence and creative agency.
Published 6 August 2026 in the South African Medical Journal, this peer-reviewed essay examines data science and medical AI through four lightly fictional but reality-informed case studies from Bamenda to Mthatha to Toronto. It argues that AI tools largely built on Western biomedical traditions may conflict with relational, spiritual and Indigenous understandings of health, manifesting as epistemic friction and diminished trust.
A bibliometric review of 722 Scopus-indexed papers from 2011 to 2024 tracked how artificial intelligence has been applied to ADHD prediction. Using Python and VOSviewer, the authors found exponential growth peaking in 2023, a concentration of output in the United States and China, and a technological shift from support vector machines to deep learning with EEG becoming the favored data modality.
By July 30 2026, a narrative review in Journal of Computer-Aided Molecular Design described the use of structural modeling and artificial intelligence for functional prediction of proteins encoded by multidrug-resistant bacterial genomes. It reported that tools such as AlphaFold and RoseTTAFold have enabled high-accuracy three-dimensional structure prediction, facilitating annotation of hypothetical proteins and identification of conserved domains and catalytic sites.
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