From Executor to Orchestrator: The Pharmacology Scientist in the Age of Agentic AI
Clinical Pharmacology &Therapeutics, Volume 120, Issue 3, Page 648-662, September 2026.Drug development productivity has not improved despite five decades of computational advancement, with the probability that a compound entering Phase I achieving regulatory approval remaining near 10%. Each automation wave increased throughput while leaving the interpretive bottleneck intact; scientists continued to formulate questions, evaluate ...
Michael McCoy, Matthew McCoy
wiley +1 more source
Two-stage authentication and key agreement protocol for commuting in Internet of vehicles
Tongxin xuebaoAiming at the security and efficiency of commuter vehicles accessing services from road side unit (RSU) in Internet of vehicles (IoV), a two-stage authentication and key agreement protocol was proposed.
ZHANG Haibo +3 more
doaj
Prediction Pipeline Selection for Incomplete Clinical Data via Missingness Fingerprints and Instance Augmentation. [PDF]
Bioengineering (Basel)Li R, Shen Z, Wu C, Li J, Tian Y.
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JCC Plus, Volume 1, Issue 5, September 2026.ABSTRACT Background and Aims Intestinal ultrasound (IUS) is used to monitor inflammatory bowel disease (IBD), but bowel wall thickness (BWT) measurements are operator dependent and hard to standardize. The aim was to develop a system for identifying the bowel wall and measuring BWT, while accounting for interobserver disagreement.
Jakob Hestbjerg Karrer +9 more
wiley +1 more source
Resilient distributed model predictive control for cooperative microgrids under communication loss with demand response integration. [PDF]
PLoS OneAlghamdi B.
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Magnetic Resonance in Medicine, Volume 96, Issue 3, Page 1313-1322, September 2026.ABSTRACT Purpose To propose a new method using a physics‐guided neural network for quantitative parameter mapping in balanced steady‐state free precession (bSSFP) imaging. Theory and Methods We trained physics‐guided neural networks with a multilayer perceptron using simulated bSSFP signals generated from tissue parameters (T1, T2,Meffc, ∆f and φRF ...
Hye‐Ryeong Choi +2 more
wiley +1 more source
Rotation-based metric on the Riemannian manifold of SPD matrices with applications to source data selection for brain-computer interface transfer learning. [PDF]
Front Hum NeurosciHeskebeck F +2 more
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Sparse Minimum Redundancy Maximum Relevance for Feature Selection
Scandinavian Journal of Statistics, Volume 53, Issue 3, Page 1134-1151, September 2026.ABSTRACT We propose a feature screening method that integrates both feature–feature and feature–target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classical mRMR penalized by a non‐convex regularizer, and where the parameters estimated as ...
Peter Naylor +3 more
wiley +1 more source
Assessing Treatment Effects in Observational Data With Missing Confounders: A Comparative Study of Practical Doubly-Robust and Traditional Missing Data Methods. [PDF]
Stat MedWilliamson BD +15 more
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Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source