Exploring the potential role of ENPP2 in polycystic ovary syndrome and endometrial cancer through bioinformatic analysis by Xumin Zhang, Jianrong Liu, Chunmei Bai, Yang Li, Yanxin Fan

“…Methods Initially, differential analysis, the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine-recursive feature elimination (SVM-RFE) algorithms were employed to identify candidate genes associated with ferroptosis in PCOS. …”
Get full text

Modeling residue formation from crude oil oxidation using tree-based machine learning approaches by Mohammad-Reza Mohammadi, Seyyed-Mohammad-Mehdi Hosseini, Behnam Amiri-Ramsheh, Saptarshi Kar, Ali Abedi, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

“…Furthermore, temperature was identified as the most influential factor affecting residual crude oil content, exhibiting a significant negative correlation, while API gravity also showed a negative impact. …”
Get full text

Deep Learning Approaches for Retinal Disease Identification in Fundus Imaging: A Comprehensive Overview by Ismael Abdulkareem Ali, Sozan Abdullah Mahmood

“…Vision impairment is becoming a major health concern, especially in elderly people. While in the medical field, manually detecting ocular pathology has significant difficulty. …”
Get full text

Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…RL-ENN stands for Reinforcement Learning-Driven Evolutionary Neural Network, while T-STFREP is a generalized acronym for Transformer-Based Spatiotemporal Forecasting. …”
Get full text

The Improved-EFI Score: A Multi-Omics-Based Novel Efficacy Predictive Tool for Predicting the Natural Fertility of Endometriosis Patients by He Q, Zhang C, Hu Y, Deng J, Zhang S

“…An improved endometriosis fertility index (EFI) predictive model was created based on ultrasound radiomics and urinary proteomics gathered during the patient’s initial admission, using two machine learning algorithms. The predictive model was evaluated for C-index, calibration, and clinical applicability through receiver working characteristic curve, decision curve analysis.Results: The improved EFI prediction model nomogram, based on five ultrasound radiomics parameters and three urine proteomics, had AUC values of 0.921 (95% CI: 0.864– 0.978) and 0.909 (95% CI: 0.852– 0.966) in the training and validation sets, respectively, while the traditional EFI prediction model had AUC values of 0.889 (95% CI: 0.832– 0.946) and 0.873 (95% CI: 0.816– 0.930) in the training and validation sets, respectively. …”
Get full text

Critical structural and functional roles for the N-terminal insertion sequence in surfactant protein B analogs. by Frans J Walther, Alan J Waring, Jose M Hernandez-Juviel, Larry M Gordon, Zhengdong Wang, Chun-Ling Jung, Piotr Ruchala, Andrew P Clark, Wesley M Smith, Shantanu Sharma, Robert H Notter

“…Gel electrophoresis demonstrated that Super Mini-B was dimeric in SDS detergent-polyacrylamide, while Mini-B was monomeric. Surface plasmon resonance (SPR), predictive aggregation algorithms, and molecular dynamics (MD) and docking simulations further suggested a preliminary model for dimeric Super Mini-B, in which monomers self-associate to form a dimer peptide with a "saposin-like" fold. …”
Get full text

Interpretable machine learning models for predicting in-hospital mortality in patients with chronic critical illness and heart failure: A multicenter study by Min He, Yongqi Lin, Siyu Ren, Pengzhan Li, Guoqing Liu, Liangbo Hu, Xueshuang Bei, Lingyan Lei, Yue Wang, Qianghong Zhang, Xiaocong Zeng

“…The MIMIC datasets served as the derivation cohort, while the eICU-CRD dataset was used for external validation. …”
Get full text

M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy by Nalini Schaduangrat, Hathaichanok Chuntakaruk, Thanyada Rungrotmongkol, Pakpoom Mookdarsanit, Watshara Shoombuatong

“…Abstract Accelerating drug discovery for glucocorticoid receptor (GR)-related disorders, including innovative machine learning (ML)-based approaches, holds promise in advancing therapeutic development, optimizing treatment efficacy, and mitigating adverse effects. While experimental methods can accurately identify GR antagonists, they are often not cost-effective for large-scale drug discovery. …”
Get full text

Semi-Implicit Numerical Integration of Boundary Value Problems by Maksim Galchenko, Petr Fedoseev, Valery Andreev, Endre Kovács, Denis Butusov

“…The known shortcoming of implicit algorithms is high computational costs, which can become unacceptable in the case of numerous right-hand side function calls, which are typical when solving boundary problems via the shooting method. …”
Get full text

Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions by Lili Zhao, Xuncheng Fan, Tao Hong

“…At the methodological level, the study systematically evaluates core algorithms for land surface temperature extraction and heat island intensity calculation, compares innovative developments in multi-source remote sensing data integration and fusion techniques, and establishes a framework for accuracy assessment and validation. …”
Get full text

SARS-COV-2 PREVALENCE IN INDIA COMPARED TO THE REST OF THE GLOBE AND ASCERTAINS EPIDEMIOLOGICAL CHARACTERISTICS ASSOCIATED WITH THE COVID-19 PANDEMIC DURING 2020 IN INDIA by M. Rajesh Kumar Rao, Rabindra N. Padhy, Manoj Kumar Das

“…Bihar had the most cases of infection, while Punjab had the most deaths.Conclusion: SARS-CoV-2 disease led India to have a lower morbidity and mortality burden than the rest of the world. …”
Get full text

Forecasting readmission in COVID-19 patients utilizing blood biomarkers and machine learning in the Hospital-at-Home program by Maria Glòria Bonet-Papell, Maria Glòria Bonet-Papell, Georgina Company-Se, María Delgado-Capel, Beatriz Díez-Sánchez, Lourdes Mateu-Pruñosa, Roger Paredes-Deirós, Jordi Ara del Rey, Lexa Nescolarde

“…Classification algorithms can aid clinicians in making informed decisions regarding patient transfers from conventional hospitalization to HaH.…”
Get full text

Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis by Dr. Muhammad Iqhrammullah, Prof. Asnawi Abdullah, Dr. Hermansyah, Fahmi Ichwansyah, Prof. Dr. Ir. Hafnidar A. Rani, Meulu Alina, Artha M. T. Simanjuntak, Derren D. C. H. Rampengan, dr. Seba Talat Al‐Gunaid, dr. Naufal Gusti, dr. Arditya Damarkusuma, Edza Aria Wikurendra

“…In a brand‐specific subgroup analysis, the algorithmic reading reached a summary area under the curve (sAUC) of 96%, while another brand achieved the highest sAUC of 98% in manual reading. …”
Get full text

Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
Get full text

A bioinspired in-materia analog photoelectronic reservoir computing for human action processing by Hangyuan Cui, Yu Xiao, Yang Yang, Mengjiao Pei, Shuo Ke, Xiao Fang, Lesheng Qiao, Kailu Shi, Haotian Long, Weigao Xu, Pingqiang Cai, Peng Lin, Yi Shi, Qing Wan, Changjin Wan

“…Incorporating physics into a bioinspired visual system is promising to offer unprecedented energy efficiency, while the mismatch between physical dynamics and bioinspired algorithms makes the processing of real-world samples rather challenging. …”
Get full text

A Super-Resolution Approach for Image Resizing of Infant Fingerprints With Vision Transformers by Joao H. P. Machado, Barbara De O. Koop, Marcelo Filipak, Marco A. C. Barbosa, Jefferson T. Oliva, Luiz Fernando Puttow Southier, Dalcimar Casanova, Marcelo Teixeira

“…For biometric identification and verification, results show an increase in the order of 10% for resized images in comparison with traditional resizing algorithms.…”
Get full text

Computational design of diverse nuclear factor erythroid 2 activators with cellular antioxidative activity by Mingyue Yuwen, Xiaoning Gao, Junli Ba, Jiayang Wu, Jun Kang, Sheng Ye, Cheng Zhu

“…Summary: Oxidative stress disrupts signaling pathways contributing to chronic diseases, while the KEAP1-NRF2 pathway is central to cellular antioxidant defenses. …”
Get full text

Metabolomics and lipidomics of plasma biomarkers for tuberculosis diagnostics using UHPLC-HRMS by Gaofeng Sun, Quan Wang, Xinjie Shan, Maierheba Kuerbanjiang, Ruiying Ma, Wensi Zhou, Lin Sun, Qifeng Li

“…Differential metabolites were screened using principal component analysis and machine learning algorithms including LASSO, Random Forest, and XGBoost. …”
Get full text

Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

“…Six machine learning algorithms—Decision Trees, k-nearest neighbors, Gaussian Support Vector Machine, Neural Network, Support Vector Machines kernel, and Logistic Regression Kernel—were evaluated for both binary and multi-class classification using feature sets of 4, 12, 23, 50, and 79 features. …”
Get full text

Integrating Remote Sensing and AI for precision Monitoring of Soil and Vegetation Contamination by M. Spiralski, A. Miszczak, G. Siebielec, Ż. Piasecka, R. Trojnacki, P. Kwaśnik, J. Kotlarz, K. A. Kubiak-Siwinska, M. Kacprzak, S. Marciniak, K. A. Rotchimmel, K. P. Beben, J. Szymanski

“…A combination of high-resolution UAV imagery, multispectral satellite data, and a suite of vegetation indices was utilized to correlate spatial variations in soil and crop conditions with pollutant concentrations. Machine learning algorithms, including Random Forest, were applied to classify contamination levels, while laboratory analyses validated the spectral findings. …”
Get full text