Results 181 to 190 of about 1,378,752 (293)

MetaPaCS: A Novel Meta‐Learning Framework for Pancreatic Cancer Subtype Identification

Advanced Intelligent Systems, EarlyView.
We have developed MetaPaCS, an ensemble meta‐learning framework for reliable prediction of pancreatic cancer subtypes with high accuracy. MetaPaCS is capable of capturing subtype‐specific distinct gene expression patterns and drug‐disease associations for pancreatic cancer.
Nick B. Peterson, Mengtao Sun, Xinchao Wu, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Physics‐Informed Machine Learning for Predicting Phases and Density of Al2O3–TiB2 Composites Synthesized via Laser Ignition From the Al–TiO2–B2O3–H3BO3 Reactive System

Advanced Intelligent Systems, EarlyView.
This interactive physics‐informed machine learning model predicts the composition and density of advanced ceramic materials produced by self‐propagating high‐temperature synthesis. The model requires user input processing parameters and demonstrates high accuracy.
Evangelos Daskalakis, Geeta Sharma, Sarathkumar Loganathan, Andrew Scott, Animesh Jha   +4 more
wiley   +1 more source

Beyond Binary: Cardiac Patterning as Probabilistic Fate Restriction. [PDF]

Bioessays
Ivanovitch K.
europepmc   +1 more source

Kinematic‐Aware Diffusion Model Correction for Human Motion Generation via Pose Transfer

Advanced Intelligent Systems, EarlyView.
Overall architecture of the proposed video kinematic pose correction pipeline. The framework integrates diffusion‐based video generation, multi‐estimator skeleton extraction, temporal Kalman smoothing, biomechanical constraint enforcement, and pose‐conditioned frame regeneration via Pose‐guided Image Synthesis and Editing. This paper presents Kinematic‐
Alaa Abdullah Albaghdadi, Ahmad R. Naghsh‐Nilchi   +1 more
wiley   +1 more source

From Atoms to Reactors: A Critical Review of a Decade of Machine Learning in Heterogeneous Catalysis (2017–2026)

Angewandte Chemie, EarlyView.
Machine learning has digitalized heterogeneous catalysis from the top of the length scale downward: prediction at the atom and the material is now mature, yet the reactor and the process remain the open frontier. This critical review traces a decade of progress across the full catalytic value chain and asks where the next decade of impact must be won ...
Rafael Larraz, Avelino Corma
wiley   +2 more sources

Learning the Boundary Between Involvement and Severity: A Multi-Target Machine-Learning Analysis of Emotion Dysregulation, Impulsivity, Gambling Involvement, and Problem Severity in Psychiatric Outpatients. [PDF]

Clin Neuropsychiatry
Vecchio AGM, Cilia ND, Maniaci G, Schimmenti A, Costanzo A.   +4 more
europepmc   +1 more source

Artificial Intelligence for Benign Esophageal Stricture Dilation: An Evidence‐Transferability Framework and Safety‐First Roadmap

AI &Innovation, EarlyView.
ABSTRACT Background Endoscopic dilation is first‐line therapy for symptomatic benign esophageal strictures but remains operator‐dependent. Artificial intelligence (AI) could support assessment, risk stratification, and documentation; however, evidence from adjacent tasks is often mistaken for procedure‐specific validation.
Ahmed A. Salman, Mohamed A. Salman
wiley   +1 more source

Lack of Evidence for Gene-Level Convergence Linked to Evolutionary Shifts in Torpor Among Placental Mammals. [PDF]

Genome Biol Evol
Kontopoulos DG, Ahmed AW, Bein B, Levesque DL, Hiller M.   +4 more
europepmc   +1 more source

Uncovering renewable energy policy impact channels on land values, the local farm structure, and farmland heterogeneity

American Journal of Agricultural Economics, EarlyView.
Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt, Stefan Seifert, Saskia Wolff, Tobia Lakes, Marten Graubner, Axel Werwatz, Silke Hüttel   +6 more
wiley   +1 more source

Phylogenetic Inference from Atomized 3D Morphometric Data: A Case Study using Kangaroos. [PDF]

Syst Biol
Celik MA, Fruciano C, Butler K, Weisbecker V, Phillips MJ.   +4 more
europepmc   +1 more source