Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
A systematic review published October 14, 2025 synthesized peer-reviewed literature from January 2020 to July 2025 on AI in nutrition and dietetics, covering dietary assessment, personalized nutrition and chronic disease management, generative AI and conversational agents, public health nutrition, sensory science, and ethics.
A peer-reviewed cross-sectional study of 358 medical students from November 2025 to January 2026 examined factors linked to attitudes toward AI using online questionnaires including digital literacy and emotional intelligence scales. Most students had used AI, but majorities reported ethical or legal concerns and worries about reduced clinical reasoning.
Researchers developed TrialTriage, a semiautonomous prescreening workflow on the n8n platform that uses large language model extraction from clinical narratives and investigator email replies plus a 7-criterion deterministic rule engine to classify phase I oncology trial eligibility, automatically emailing investigators when information is missing and reclassifying after reply capture.
A retrospective study at Tohoku University Hospital applied an ensemble of five machine learning algorithms to 4,574 spinal anesthesia cases from 2010 to 2022, using propensity score matching to compare 269 patients with PONV to 269 without, to predict and explain postoperative nausea and vomiting within 24 hours.
In an online experiment reported July 12 2024, researchers gave some writers LLM-generated story ideas and had independent evaluators rate the resulting short stories. By that date they observed that access to AI ideas caused higher ratings for creativity, writing quality, and enjoyment, especially for less creative writers.
Published 2024-08-19, this peer-reviewed article argues that AI's impact on human rights extends beyond discrete violations to a deeper attritional degradation. Using the concept of slow violence, it contends individuals lose capacity to comprehend and contest AI-driven harms, discrete rights lose their normative justifications, and even broad notions of human dignity fail to capture new challenges
As of August 4, 2024, this peer-reviewed survey in Sensors reviewed early trends in using large language models such as GPT-4 and Llama to model vast wearable sensor data for human activity recognition, health monitoring, and behavioral modeling, integrating them with time series and deep learning methods.
A February 2026 review in Biosensors summarizes how lab-on-a-chip systems have been advanced through 3D printing, modular substrates, and biosensor integration, and how coupling with AI and machine learning has created smart platforms for cancer diagnostics, infectious disease detection, point-of-care testing, and therapeutic monitoring.
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