Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
By August 2026, a Histopathology study re-examined fallopian tube tissue from 19 BRCA1/2 carriers who had undergone risk-reducing salpingo-oophorectomy around age 40. Using deeper sections cut at 150 μm intervals and a deep learning model to support STIC detection, the team found occult STIC or HGSC in all patients who later developed peritoneal HGSC despite having no STIC or HGSC at initial diagnosis.
Researchers developed a novel oxidative stress index score from liver enzyme biomarkers and built machine learning models to predict disease-free survival and overall survival in 970 locally advanced rectal cancer patients treated at Sun Yat-Sen University Cancer Center. The training cohort received total neoadjuvant therapy and the validation cohort received neoadjuvant chemoradiotherapy, followed by surgery.
On September 2025, the CODEX Action Incubator at UCSF brought together 30 stakeholders from health systems, patient advocacy, industry and policy to address how to measure AI's effect on diagnostic excellence. Participants focused on AI scribes and, via a modified Delphi process, narrowed 17 candidate measures to two priority metrics tied to primary care physician usage rates: timely follow-up of abnormal breast and colorectal cancer screening results and patient-reported diagnostic experience.
Researchers developed a capability-based framework to analyze where artificial intelligence and generative AI fit into supply chain and operations management. Using capabilities like learning, perception, prediction, interaction, adaptation and reasoning, they mapped applications across 13 decision areas including demand forecasting, inventory management, supply chain design and risk management.
By December 2025, a peer-reviewed review in Discover Psychology examined how Cognitive Behavioral Therapy has been integrated into emotional AI systems, including chatbots and large language models, to detect mental health issues and deliver guided self-reflection and cognitive restructuring.
Researchers surveyed 226 undergraduate and postgraduate students at major universities in Mogadishu to examine how over-reliance on AI relates to learning outcomes, and how ethical concerns and institutional policies moderate that relationship.
This PNAS perspective from May 2024 argues that generative AI capable of realistic text and image generation could enhance social science research methods. It points to survey research, online experiments, automated content analysis, and agent-based models as areas where such tools might improve study of human behavior.
A December 2025 systematic review of 40 articles from 2015-2025 examined how AI is used in bi/multilingual education, focusing on personalized learning, intelligent tutoring systems and chatbots, and automated assessment. It reported that adaptive feedback and real-time analytics were associated with higher student engagement, learning performance and teaching efficiency in multiliteracy language learning.
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