Results 221 to 230 of about 61,045 (270)

Revisiting the LSER Approach in the Era of Machine Learning: Insights from IAM Chromatography. [PDF]

Mol Pharm
Nisterenko W, Greber KE, Kierkowicz M, Ciura K.   +3 more
europepmc   +1 more source

Real‐World Effectiveness and Safety of Sofosbuvir‐Based Therapy in Chinese Children and Adolescents With Chronic HCV Infection: A Retrospective Multicentre Study

Journal of Viral Hepatitis, Volume 33, Issue 12, December 2026.
ABSTRACT Few direct‐acting antiviral regimens are approved in China for children and adolescents with chronic hepatitis C virus (HCV) infection and data are limited on their efficacy and safety in this population. This retrospective, multi‐centre study aimed to assess the real‐world effectiveness and safety of ledipasvir/sofosbuvir (LDV/SOF) and ...
Li Liu, Mei Li, Shishu Zhu, Yi Dong, Hongmei Zu, Ping Yu, Ruiling Liu, Yan Chen, Joshua Lin, Carl Gustafson, Heribert Ramroth, Lin Liu, Yanwen Luo   +12 more
wiley   +1 more source

Clinical Characteristics of Coccidioidomycosis in Patients with Hepatitis C-Associated Cirrhosis. [PDF]

Microorganisms
Shepard R, Nukala N, Roytman M, Policepatil S, Sivasubramanian G.   +4 more
europepmc   +1 more source

Direct Comparison Between Loss‐to‐Follow‐Up and Statistical Fragility Is Methodologically Inappropriate, and Fragility Reflects the P Value, Not Trial Robustness: A Simulation Analysis of 300,000 Randomized Controlled Trials

Arthroscopy, Volume 42, Issue 11, Page 2749-2758, November 2026.
Purpose To assess the relation between the fragility index (FI) and reverse fragility index (RFI) with the minimum number of patients needed to reverse statistical significance (e.g. henceforth termed the lost to follow‐up index (LTFI) and reverse LTFI (R‐LTFI), respectively) and apply machine learning to identify which trial parameters are most ...
Prushoth Vivekanantha, Helena Son, Jeffrey Kay, Satyavenkata Kotipalli, Marc Daniel Bouchard, Kim Madden, Nicole Simunovic, Olufemi R. Ayeni   +7 more
wiley   +1 more source

Improving corrosion depth estimation in buried pipelines using SMOTE-integrated machine and deep learning models. [PDF]

PLoS One
AlOmar MK, Hameed MM, Ali OK, Samir AA, Kukreja T, Masood A, Salem A.   +6 more
europepmc   +1 more source

Machine Learning‐Based PAT Tool for Real‐Time Residual Moisture Monitoring in Lyophilized Biopharmaceuticals Using NIR Spectroscopy

Biotechnology and Bioengineering, Volume 123, Issue 11, Page 3030-3046, November 2026.
ABSTRACT There is a growing demand in the pharmaceutical industry to optimize analytical methodologies, reducing time and resource consumption while ensuring rapid process development and cost‐efficient manufacturing. Indeed, Food and Drug Administration (FDA) introduced the Process Analytical Technology (PAT) as an initiative enabling manufacturers to
Samuele Fiorenza, Mariapia D'Urso, Ambra Massei, Nunzia Falco, Davide Fissore, Enza Torino   +5 more
wiley   +1 more source

Carbon‐Based Adsorbents for CO2 Capture: Mechanism‐Guided Material Design and Data‐Driven Optimization

Carbon Neutralization, Volume 5, Issue 6, November 2026.
The main purpose of this review is to summarize recent progress in the broad family of carbon‐based materials and their derivatives for CO2 capture. Rather than focusing on a single precursor or modification route, it examines pristine carbon adsorbents, functionalized carbon derivatives, and carbon‐based composites within a unified framework.
Jinliang Cai, Jianchao Zhang, Zhiyong Peng, Yihe Miao, Jialing Xu   +4 more
wiley   +1 more source

Development of a Machine Learning Model to Predict Short Duration HCV Treatment Response. [PDF]

J Viral Hepat
Carson JM, Barbieri S, Verich A, Tu E, Lloyd A, Dore GJ, Matthews GV, Martinello M.   +7 more
europepmc   +1 more source