Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Researchers developed a multimodal MRI-based deep learning model to non-invasively identify germinomas among pineal region tumors before surgery. Using 114 pathologically confirmed cases divided into training and test sets, a CNN with contrastive learning and a mixed-attention fusion of MRI sequences and demographic data was evaluated against single-modality models.
On 2026-08-17, a review in Graefe's Archive summarized automated diabetic retinopathy detection and classification using fundus images, surveying ML, DL and hybrid methods, their datasets, pre-processing and metrics, and noting newer ensemble, transformer and attention approaches.
Researchers tested an AI-powered virtual patient application built on ChatGPT to teach Mental Status Examination skills to 27 psychiatric nursing internship students. Using a sequential explanatory mixed-methods design, they measured competency before and after the structured prompting intervention and then interviewed 18 students about their experience.
Researchers developed a hybrid quantum-classical machine learning approach that pairs variational quantum circuits with the ESM2 protein language model in a prototypical network to predict binding partners of Intrinsically Disordered Regions across multiple classes including proteins, nucleic acids, lipids, and metal ions.
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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