Results 171 to 180 of about 41,191 (306)

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

AIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

Heavy metals and prevalence of sexually transmitted infections: a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) 2003-2016. [PDF]

BMC Infect Dis
Taylor BD, Noah A, Adekanmbi V, Zhang Y, Ingle M, Berenson A.   +5 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Progressive myocardial metabolic dysfunction after stereotactic arrhythmia radioablation for ventricular tachycardia in hypertrophic cardiomyopathy: a serial multimodality imaging case report. [PDF]

Eur Heart J Case Rep
Shimojo M, Kawamura M, Inden Y, Naganawa S, Murohara T.   +4 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Extraskeletal osteosarcoma in the rectus abdominis muscle: a case report. [PDF]

J Surg Case Rep
Nakayama K, Ueda H, Fukaya K, Shimomura K, Konishi E, Osawa T.   +5 more
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Characterization of Next-Generation Inhibitors for the Inward-Rectifier Potassium Channel K_ir2.1: Discovery of VU6080824. [PDF]

ACS Med Chem Lett
Duncan RA, Haymer DH, Lazarenko RM, Li L, Blackwell Y, Days EL, Krishnan S, Gray AT, Boutaud O, Engers DW, Lindsley CW, Denton JS, Bender AM.   +12 more
europepmc   +1 more source

Clinically Informed Intelligent Classification of Ovarian Cancer Cells by Label‐Free Holographic Imaging Flow Cytometry

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone, Beatrice Cavina, Daniele Gaetano Sirico, Martina Mugnano, Vittorio Bianco, Lisa Miccio, Anna Myriam Perrone, Anna Maria Porcelli, Giuseppe Gasparre, Ivana Kurelac, Pasquale Memmolo, Pietro Ferraro   +11 more
wiley   +1 more source

Association of urinary metal exposure with H. pylori seropositivity and mortality in the U.S. Population: NHANES 1999-2000 analysis. [PDF]

BMC Gastroenterol
Meng XD, Xiong YJ, Yang S.
europepmc   +1 more source