Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
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.
Researchers developed a dynamic joint prediction system for incomplete immune reconstitution risk in people living with HIV using Bayesian joint modeling of longitudinal CD4+ counts and CD4/CD8 ratios from 21,862 patients across 31 Chinese provinces between 2003 and 2024.
On August 5, 2026, a peer-reviewed study in JCO Oncology Practice evaluated AI translation of three oncology clinical trial informed consent forms from English to Spanish, comparing DeepL Pro, ChatGPT-4o, and a medically trained model Med_English2Spanish against certified translations using five equivalence domains scored by two bilingual physicians.
By November 2024, researchers tested prompt engineering as a creative skill for AI art in three studies with crowdsourced participants, asking them to judge prompt quality, write prompts, and refine them.
Published November 30, 2024, this peer-reviewed article reviews how combining genomics, transcriptomics, proteomics and metabolomics with machine learning and high-throughput sequencing is being used to tailor therapies to individual genetic and molecular profiles.
A systematic literature review published November 28, 2024 examined how artificial intelligence is transforming organizational landscapes. It found AI reshapes work practices through automation and changes to decision making and employee roles, while driving cultural shifts toward innovation, agility, and continuous learning.
By July 2026, a narrative review of 40 studies from 2020-2025 found deep learning, led by U-Net variants with residual and attention mechanisms and standardized pipelines like nnU-Net, increasingly achieved high Dice scores on MRI DWI/ADC, with many reports above 0.80 and recent transformer and ensemble multisite models approaching 0.90, while CT performance was lower and more variable.
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