Results 221 to 230 of about 28,744 (310)

CSGM: A R Package to Conduct a Robust Cross‐Sectional Geometric Morphometric Analysis

American Journal of Biological Anthropology, Volume 190, Issue 1, May 2026.
ABSTRACT Objective Evaluating the relationships between the shape and biomechanical function of bone cross‐sections can contribute novel insights towards human functional and evolutionary morphology. However, this research involves unique analytical and statistical challenges when comparing complex and multidimensional shape data to multivariate ...
Brian A. Keeling, Alessandro Urciuoli, Mercedes Conde‐Valverde, Julia Diez‐Valero, Laure Spake, Rolf Quam   +5 more
wiley   +1 more source

Circulating MicroRNA Biomarkers for Chronic Pain and Acupuncture Response: An Exploratory High-Dimensional Small-Sample Study. [PDF]

J Pain Res
Kang IH, Kim SN.
europepmc   +1 more source

Elastic Net Regularized Gaussian Copula Regression for Mixed Outcomes: R Codes and Data

Huma Rani, Tahir Mehmood, Muhammad Aslam, Laila A. AL Essa   +3 more
openalex   +1 more source

Individualized Treatment in Distal and Medium Vessel Occlusion Stroke Using a Validated Explainable Counterfactual Treatment Estimation Model

Annals of Neurology, Volume 99, Issue 5, Page 1198-1209, May 2026.
Objective The optimal treatment for distal medium vessel occlusion (DMVO) stroke remains uncertain, and evidence comparing endovascular therapy (EVT) with medical management (MM) is limited. We aimed to develop and validate a predictive modeling tool to assess individual treatment benefit in DMVO stroke using explainable counterfactual treatment ...
Mohamed F. Doheim, Mahmoud H. Mohammaden, Hend Abdelhamid, Marta Olive‐Gadea, Marc Rodrigo‐Gisbert, Manuel Requena, Johanna T. Fifi, James E. Siegler, Santiago Ortega‐Gutierrez, Mohamad Abdalkader, Ali Alaraj, Wei Hu, Thanh N. Nguyen, Diogo C. Haussen, Raul G. Nogueira   +14 more
wiley   +1 more source

Deep learning-based optimization for accurate multimodal medical image registration. [PDF]

Sci Rep
Chouksey P, Kashyap M, Subbarao A.
europepmc   +1 more source

Clinically Deployable Handwriting Biomarkers of Parkinson's Disease via Multiscale Attention and Bayesian–Genetic Optimization

Brain and Behavior, Volume 16, Issue 5, May 2026.
Tablet‐based handwriting tasks (spiral, meander, and wave) are transformed into unified images and analyzed using PD‐MGMA‐DSCNN, a lightweight multiscale gated attention network. Bayesian–genetic optimization improves performance, while SHAP attribution maps provide interpretable handwriting biomarkers for Parkinson's disease screening.
Khosro Rezaee, Ali Khalili Fakhrabadi
wiley   +1 more source

Digital Technologies Disclosure and the Cost of Capital: The Mediating Role of Sustainability Performance

Business Strategy and the Environment, Volume 35, Issue 4, Page 5895-5925, May 2026.
ABSTRACT This study examines the economic consequences of Digital Technologies Disclosure (DTD), focusing on its impact on the cost of capital. The increasing significance of digital transformation in shaping corporate strategies and market perceptions motivates the study.
Hussein Mohsen Saber Ahmed, Awad Elsayed Awad Ibrahim, Khaldoon Albitar   +2 more
wiley   +1 more source

Decoding Emotional Signatures of Ethical Ads: An Analysis of Actor‐Viewer Synchrony

Journal of Consumer Behaviour, Volume 25, Issue 3, Page 1061-1077, May 2026.
ABSTRACT We examine whether ethical advertisements differ from conventional ads in their on‐screen emotional signatures and whether those signatures transfer to actor‐viewer synchrony. Study 1 analyses 138 professionally produced YouTube ads using Automated Facial Expression Recognition (AFER) and Convolutional Neural Networks (CNN) to quantify actor ...
Vik Naidoo, Nicolas Hamelin
wiley   +1 more source

Predicting infected pancreatic necrosis in acute pancreatitis using machine learning models and feature selection. [PDF]

Sci Rep
Xin L, Yixuan D, Bohan H, Yunheng S, Hairong L, Feng C, Tong Y, Fei L, Xiaolu F, Jia L.   +9 more
europepmc   +1 more source

A Comparison of Machine Learning Algorithms for Predicting Hypertension Incidence Based on Cohort Study

Endocrinology, Diabetes &Metabolism, Volume 9, Issue 3, May 2026.
This 10‐year cohort study (MASHAD) including 8237 participants without baseline hypertension used machine learning to predict hypertension incidence. Over follow‐up, 2548 individuals developed hypertension. Among five algorithms tested, XGBoost performed best (AUC‐ROC: 79%, Accuracy: 74%). Key predictors identified by SHAP analysis included copper, BMI,
Somayeh Ghiasi, Susan Darroudi, Mina Moradi, Farzam Kamrani, Muhammad Reza Fatehi, Seyed Masih Sajjadi, Sara Yousefian, Sara Amiri, Majid Ghayour‐Mobarhan, Vahid Mahdavizadeh, Jalal A. Nasiri, Amin Mansoori, Habibollah Esmaily   +12 more
wiley   +1 more source