Results 171 to 180 of about 35,671 (228)

Fibrotic, metabolic and clinical improvements in patients with chronic hepatitis C treated with direct-acting antiviral therapy in a resource limited setting: a prospective cohort study. [PDF]

BMC Gastroenterol
Ekubazgi KW, Dellil M, Woldegeorgis BZ, Berhane KA, Anagaw S, Fisseha H.   +5 more
europepmc   +1 more source

Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare, Esmaeil S. Nadimi, U. Rajendra Acharya, Victoria Blanes‐Vidal   +3 more
wiley   +1 more source

Machine learning-based QSPR modeling for predicting the <i>n</i>-octanol/air partition coefficient of polybrominated diphenyl ethers. [PDF]

iScience
Wu W, Chen H, Liu Z, Yan W, Wu D, Chen J, Liu J, Xing Z.   +7 more
europepmc   +1 more source

A GEO‐LEO Imager Data Set for Characterizing Rapid Changes of Global Aerosol Properties

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 15, 16 August 2026.
Abstract Aerosols, the ubiquitous small particulates in our atmosphere, have climate, air quality, and/or other impacts far from their original sources. The Dark Target Algorithm (DTA), originally developed for retrieving aerosol properties from satellite imagers in Low‐Earth Orbit (LEO), has been ported to imagers in Geostationary (GEO) orbit. Using a
R. C. Levy, P. Gupta, Y. R. Shi, L. A. Remer, M. Kim, M. M. Oo, J. Wei, V. R. Sawyer, V. P. Kiliyanpilakkil, R. E. Holz, B. Ramachandran, R. B. Pierce, S. Mattoo   +12 more
wiley   +1 more source

Efficient quantum algorithm for the design of complex materials: quantum circuit learning. [PDF]

Sci Rep
Osaki S, Hoshitani K, Nakamura M, Kimura K, Yamamoto T.   +4 more
europepmc   +1 more source

Developmental and Phenotypic Outcomes in Mild Phenylalanine Hydroxylase Deficiency

American Journal of Medical Genetics Part A, Volume 200, Issue 8, Page 1814-1820, August 2026.
ABSTRACT Benign hyperphenylalaninemia (bHPA) is defined as elevated phenylalanine (Phe) levels remaining ≤ 360 μmol/L (6 mg/dL) and not requiring medical intervention. Individuals with bHPA may demonstrate a rise in their Phe levels > 360 μmol/L, effectively developing a mild PKU phenotype requiring therapy to prevent neurocognitive complications. This
Aaron Williams, Kristian Divin, Lindsay C. Burrage, William J. Craigen, Fernando Scaglia, Claudia Soler‐Alfonso, V. Reid Sutton, Kevin E. Glinton, Ronit Marom   +8 more
wiley   +1 more source

Assessment of machine learning models for predicting the deflection of concrete beams. [PDF]

Sci Rep
Sivasuriyan A, Vijayan DS, Trach R, Bayat H, Góral A, Piętocha A, Koda E.   +6 more
europepmc   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, Volume 104, Issue 8, Page 4079-4100, August 2026.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Estimation of chlorophyll content in cotton leaves using UAV RGB imagery. [PDF]

Front Plant Sci
Huang Y, Fan Z, Wu W, Wu H, Liu Y, Wang Q, Zhang X, Li M, Duan X, Gao Z, Wang T.   +10 more
europepmc   +1 more source

Impact of Iridium Crucible Aging on Cz‐YAG Crystal Quality and Process Economy: A Data‐Driven Study

Crystal Research and Technology, Volume 61, Issue 8, August 2026.
Machine learning models trained on CFD‐generated data reveal how iridium crucible aging influences key Czochralski YAG crystal growth outcomes. Interpretable analyses uncover the dominant role of iridium loss and its interactions with process variables, enabling accurate prediction of heating power, interface shape, and the ratio of growth rate to ...
Natasha Dropka, Xiao Le Ye, Kunal Meshram, Debajyoti Biswas, Martin Holena   +4 more
wiley   +1 more source