Results 211 to 220 of about 73,492 (280)

Machine Learning-Based Risk Stratification for Sudden Cardiac Death Using Clinical and Device-Derived Data. [PDF]

Sensors (Basel)
Ivandic H, Pervan B, Puljevic M, Velagic V, Jovic A.   +4 more
europepmc   +1 more source

Support Vector Machine Ensemble for Crude Oil Classification

Journal of Chemometrics, Volume 40, Issue 4, April 2026.
ABSTRACT The study focuses on proposing a new machine learning approach to classify crude oil samples based on their physicochemical properties, such as sulfur concentration (S), total acidity number (TAN), and American Petroleum Institute (API) gravity.
Maria Carolina da V. A. Barboza, Márcia Helena Cassago Nascimento, Gabriely Silveira Folli, Junio R. Botelho, Rafael de Queiroz Ferreira, Wanderson Romão, Paulo Roberto Filgueiras   +6 more
wiley   +1 more source

XGBoost outperforms other machine learning models in diagnosing Sepsis-Associated Thrombocytopenia: a multicenter retrospective study. [PDF]

Front Med (Lausanne)
Emir B, Ozmen E, Kilincer Bozgul SM, Acar C, Soyer N, Bozkurt D, Gonderen K, Efgan MG.   +7 more
europepmc   +1 more source

DNA‐ and RNA‐based microbial community diversity and composition in a deep agricultural subsurface environment

Ecosphere, Volume 17, Issue 4, April 2026.
Abstract Analysis of microbial community compositions in subsurface environments is essential because microbes significantly influence biogeochemical processes, including carbon storage, nutrient cycling, and groundwater quality. Many previous studies have relied on DNA‐based methods, which provide a robust taxonomic identification but can also ...
Han‐Suk Kim, Kanghyun Park, Jeongdae Im, Man Jae Kwon   +3 more
wiley   +1 more source

A global twitter sentiment analysis model for COVID-vaccination. [PDF]

Sci Rep
Chakrabarty D, Chatterjee S, Mukhopadhyay A.   +2 more
europepmc   +1 more source

A Smartphone and Web‐Based Automated Platform for Segmenting Urinary Tract Infection Using a Deep Learning‐Based Approach

Engineering Reports, Volume 8, Issue 4, April 2026.
This study presents a deep learning–powered urinary sediment analysis system designed to operate on both web and mobile platforms. At its core is a UNet++ multi‐class segmentation model trained to identify various sediment types, including background, rod, red blood cells, white blood cells, yeast, miscellaneous, single epithelial cell, small ...
Justice Williams Asare, Lukman Hamza, Pious Ackon, Kingsley Buabeng, Emmanuel Akwah Kyei, Martin Mabeifam Ujakpa, William Leslie Brown‐Acquaye, Emmanuel Freeman   +7 more
wiley   +1 more source

Urban built-up area extraction using triangle threshold algorithm and Naive Bayes classification model with multidata fusion. [PDF]

Sci Rep
Li Y, Zhong X, Liu H, Liao M, Lu YF, Liu B.   +5 more
europepmc   +1 more source

Machine Vision–Based Insect Recognition in Agriculture: A Comprehensive Review

Engineering Reports, Volume 8, Issue 4, April 2026.
This study explores machine vision for automated insect recognition in agriculture, leveraging deep learning and IoT integration. The review highlights real‐time pest detection methods, enhancing crop protection with minimal pesticide use. Comparative analysis of classifiers provides insights into performance and future advancements in sustainable ...
Mohammad Monirul Islam, Morium Akter, Mohammad Shorif Uddin, Md. Ataur Rahman, Md. Tarek Habib   +4 more
wiley   +1 more source

Development of machine learning models to identify potentially active compounds against tuberculosis. [PDF]

Sci Rep
Rawat A, Gupta S, Pal C, Chowdhury S.
europepmc   +1 more source

Clinical Discovery and Molecular Analysis of Two Novel MSH2 Gene Mutations (p.Ala771Gly and p.Val797Gly) in Saudi Colorectal Cancer Patients: Potential Implications for Tumorigenesis

Health Science Reports, Volume 9, Issue 4, April 2026.
ABSTRACT Background and Aims Colorectal cancer (CRC) is a serious global health problem, ranking first in men and third in women among all cancers worldwide. The genetic basis for CRC remains unclear in most cases; therefore, the present study aimed to investigate the molecular genetic basis of CRC and correlate it with disease outcomes.
Mahmood Rasool, Absarul Haque, Mohammed Alharthi, Tainus Ali, Sajjad Karim, Loubna Siraj Mira, Fahd Al‐Abbasi, Murad Aljiffry, Mohammed Ghunaim, Abdulrahman Sibiany, Peter Natesan Pushparaj   +10 more
wiley   +1 more source