Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

“…Notably, this surpasses the capabilities of other models that rely on amalgamations of machine learning algorithms and feature dimensionality reduction methods. …”
Get full text

Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements by Evgenii Kanin, Alsu Garipova, Sergei Boronin, Vladimir Vanovskiy, Albert Vainshtein, Andrey Afanasyev, Andrei Osiptsov, Evgeny Burnaev

“…We also provide recommendations for further development of the proposed algorithm to account for geological realism.…”
Get full text

Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database by Lin Xu, Xuejing Li, Na Zhang, Chunmei Guo, Pan Wang, Min Gao, Yanhui Zhang, Lixin Zhao

“…Utilizing the formula ln[(triglycerides mg/dl) × (glucose mg/dl)/2], the TyG index was calculated. The Boruta algorithm and Xgboost model were used for feature selection in order to pinpoint the important variables affecting results. …”
Get full text

Validation of ICD‐10 Consensus Code Set for Cirrhosis Detection Using Electronic Health Records in an Asian Population by Jason Pik‐Eu Chang, Hong‐Yi Lin, Pooi‐Ling Loi, Jeanette Pei‐Xuan Ng, Marianne De Roza, Rahul Kumar, Hiang‐Keat Tan, Chanda Kendra Ho, Wei‐Quan Teo, Amber Hwa Hwa Chung, Prema Raj

“…We evaluated the consensus code set's sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in identifying cirrhosis cases. …”
Get full text

Identification and validation of endoplasmic reticulum autophagy-related potential biomarkers in periodontitis by Ruyue Wang, Jinyue Hu, Qing Sun, Shuixiang Guo, Gege Zhang, Ao Lu, Shuo Liu, Xue Yang, Lina Wang

“…The CIBERSORT deconvolution algorithm was used to study the link between potential biomarkers and distinct types of immune cells. …”
Get full text

Vital Sign and Biochemical Data Collection Using Non-contact Photoplethysmography and the Comestai Mobile Health App: Protocol for an Observational Study by Gianvincenzo Zuccotti, Paolo Osvaldo Agnelli, Lucia Labati, Erika Cordaro, Davide Braghieri, Simone Balconi, Marco Xodo, Fabrizio Losurdo, Cesare Celeste Federico Berra, Roberto Franco Enrico Pedretti, Paolo Fiorina, Sergio Maria De Pasquale, Valeria Calcaterra

“…In addition, the app will facilitate big data collection to enhance the algorithm’s performance in measuring hemoglobin, glycated hemoglobin, and total cholesterol. …”
Get full text

Objective dairy cow mobility analysis and scoring system using computer vision–based keypoint detection technique from top-view 2-dimensional videos by Shogo Higaki, Guilherme L. Menezes, Rafael E.P. Ferreira, Ariana Negreiro, Victor E. Cabrera, João R.R. Dórea

“…In addition, the study determined the potential of a machine learning classification model to predict mobility scores based on the newly extracted mobility variables. …”
Get full text

Modeling, optimization, and thermal management strategies of hydrogen fuel cell systems by Abubakar Unguwanrimi Yakubu, Liu Qingsheng, Meng Kai, Chen Jinwei, Omer Abbaker Ahmed Mohammed, Jiahao Zhao, Qi Jiang, Xuanhong Ye, Junyi Liu, Qinglong Yu, Muhammad Aurangzeb, Shusheng Xiong

“…This review synthesizes over one hundred studies published between 2015 and 2025, highlighting advancements in steady-state and dynamic modeling, AI-driven multi-objective optimization, and integrated thermal management. Optimization algorithms such as PSO, WOA, MIGA, and NSGA-II have shown promising results, including up to 15 % reduction in hydrogen consumption and 20 to 30 % improvement in thermal uniformity. …”
Get full text

Genome-wide profiling of circulating microRNAs in adolescent idiopathic scoliosis and their relation to spinal deformity severity, and disease pathophysiology by Nasrin Khatami, Iurie Caraus, Mahamuda Rahaman, Evguenia Nepotchatykh, Mohamed Elbakry, Wesam Elremaly, Anita Franco, Marie Beauséjour, Anne-Marie Laberge, Stefan Parent, Hubert Labelle, Carl-Éric Aubin, Jean Lachaine, Alain Moreau

“…After optimization and the application of Random Forest Models a panel of six miRNAs (miR-1-3p, miR-19a-3p, miR-19b-3p, miR-133b, miR-143-3p, and miR-148b-3p) out of 15 led us to develop an algorithm predicting the risk of developing a severe scoliosis with great accuracy (100%), sensitivity (100%) and specificity (100%). …”
Get full text

Potential Herb-Drug Interactions Among Elderly Nursing Home Residents in Romania by Hanna Sebesi, László István Bába, Melinda Kolcsár, Zsolt Gáll, Soma Dávid

“…AIM: Our study investigates the algorithm-predicted HDIs during herb-drug coadministration among elderly patients in nursing homes in a Romanian sample. …”
Get full text

Unveiling the power of high-dimensional cytometry data with cyCONDOR by Charlotte Kröger, Sophie Müller, Jacqueline Leidner, Theresa Kröber, Stefanie Warnat-Herresthal, Jannis Bastian Spintge, Timo Zajac, Anna Neubauer, Aleksej Frolov, Caterina Carraro, DELCODE Study Group, Frank Jessen, Simone Puccio, Anna C. Aschenbrenner, Joachim L. Schultze, Tal Pecht, Marc D. Beyer, Lorenzo Bonaguro

“…The comprehensive suite of features of cyCONDOR, including guided pre-processing, clustering, dimensionality reduction, and machine learning algorithms, facilitates the seamless integration of cyCONDOR into clinically relevant settings, where scalability and disease classification are paramount for the widespread adoption of HDC in clinical practice. …”
Get full text

Multi-Camera Machine Learning for Salt Marsh Species Classification and Mapping by Marco Moreno, Sagar Dalai, Grace Cott, Ben Bartlett, Matheus Santos, Tom Dorian, James Riordan, Chris McGonigle, Fabio Sacchetti, Gerard Dooly

“…This demonstrates that data fusion and band reduction techniques improve species differentiation, particularly for vegetation with overlapping spectral signatures. …”
Get full text

From data to nutrition: the impact of computing infrastructure and artificial intelligence by Pierpaolo Di Bitonto, Michele Magarelli, Pierfrancesco Novielli, Donato Romano, Domenico Diacono, Lorenzo de Trizio, Angelo Mariano, Claudia Zoani, Riccardo Ferrero, Alessandra Manzin, Maria De Angelis, Roberto Bellotti, Sabina Tangaro

“…Additionally, it explores the concept of open data sharing and the integration of machine learning algorithms in the food industry to enhance food safety and product development. …”
Get full text

Amygdala activity for the modulation of goal-directed behavior in emotional contexts. by Kazutaka Maeda, Jun Kunimatsu, Okihide Hikosaka

Get full text

A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

“…In low Signal-to-Noise Ratio (SNR) conditions, various approaches and algorithms are applied to improve speech quality and intelligibility. …”
Get full text

Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi, Junichi Asaumi

“…MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. …”
Get full text

Artificial intelligence in nursing: an integrative review of clinical and operational impacts by Salwa Hassanein, Salwa Hassanein, Rabie Adel El Arab, Rabie Adel El Arab, Amany Abdrbo, Mohammad S. Abu-Mahfouz, Mastoura Khames Farag Gaballah, Mohamed Mahmoud Seweid, Mohamed Mahmoud Seweid, Mohammed Almari, Husam Alzghoul

“…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”
Get full text

Admission testing for higher education: A multi-cohort study on the validity of high-fidelity curriculum-sampling tests. by A Susan M Niessen, Rob R Meijer, Jorge N Tendeiro

Get full text

Scalable Clustering of Complex ECG Health Data: Big Data Clustering Analysis with UMAP and HDBSCAN by Vladislav Kaverinskiy, Illya Chaikovsky, Anton Mnevets, Tatiana Ryzhenko, Mykhailo Bocharov, Kyrylo Malakhov

“…The study aims to apply unsupervised clustering algorithms to ECG data to detect latent risk profiles related to heart failure, based on distinctive ECG features. …”
Get full text

Trade-Offs Between Simplifying Inertial Measurement Unit–Based Movement Recordings and the Attainability of Different Levels of Analyses: Systematic Assessment of Method Variations... by Manu Airaksinen, Okko Räsänen, Sampsa Vanhatalo

“…The IMU data can be used for an algorithmic detection of different postures and movements, which may support more detailed assessments of complex behaviors, such as daily activities. …”
Get full text