The power, potential of real-world data in randomized controlled trials: proceedings from a multistakeholder think tank.
Exploring real-world data’s role in RCTs: enhancing recruitment, safety, and regulatory approval. π€π
April 11, 2026
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Discover the newest research about AI innovations in π€ Machine Learning.
From non-agentic large language models to multi-agent systems in emergency medicine: a scoping review.
Exploring LLMs in emergency medicine: 35 studies reveal gaps in workflow integration and evaluation methods. ππ
April 11, 2026
Code-Based Versus AutoML Methods for Pill Recognition in Clinical Settings: Comparative Performance Study.
Pill recognition accuracy varies: YOLO11 (80.83%) vs. Google Vertex AI (91.60%). Cost and performance trade-offs matter! ππ
April 11, 2026
A Latent Variable Approach for Causal Effect Estimation Under Misclassified Treatment Assignment.
Latent variable methods enhance causal effect estimation in misclassified treatment scenarios, improving reliability without validation data. ππ
April 10, 2026
AI-Driven Protein Design Enhances Development of Intracellular Antibodies
AI-driven protein design improves the creation of stable intracellular antibodies, aiding diagnostics and biomedical research. π§¬π¬
April 10, 2026
Systems biology in the era of AI: “winter” or “evolution”?
Exploring AI’s impact on systems biology: a pivotal shift or mere stagnation? π€π¬ Insights from Helmy & Selvarajoo’s research.
April 10, 2026
EcoRxAgent: an AI agent for generating economically substitutable prescriptions.
AI-driven EcoRxAgent reduces prescription costs by 14.40% to 40.14% while ensuring therapeutic efficacy. ππ€
April 9, 2026
MaxGRNet: A multi-axis vision transformer with improved generalization for eye disease classification using explainable AI with insertion-deletion operations on fundus images.
MaxGRNet: Eye disease classification achieves 96.75% accuracy using multi-axis vision transformers and explainable AI. ποΈπ
April 9, 2026
Hybrid deep learning and feature selection approach for autism detection from rs-fMRI data.
Hybrid deep learning enhances autism detection accuracy to 73% using rs-fMRI data. Significant implications for diagnosis! π§ π
April 8, 2026
Internally Validated Logistic Regression Nomogram for Depressive Symptoms Risk Prediction in Middle-Aged and Older Adults With Sarcopenia: Cross-Sectional Study.
Logistic regression model predicts depressive symptoms in sarcopenic adults. AUC 0.794, Brier score 0.065. Key factors identified. ππ§
April 7, 2026