Dynamic Heart Rate Variability Vector and Premature Ventricular Contractions Patterns in Adult Hemodialysis Patients: A 48 h Risk Exploration by Gabriel Vega-Martínez, Francisco José Ramos-Becerril, Josefina Gutiérrez-Martínez, Arturo Vera-Hernández, Carlos Alvarado-Serrano, Lorenzo Leija-Salas

“…This study involves 4-h electrocardiographic records from the Telemetric and Holter ECG Warehouse (THEW) project database to analyze the dynamics in heart rate variability (HRV) indices of 51 patients with CKD. It proposes three algorithms to process long-term electrocardiography records: QRS complex and R-wave detection, premature ventricular contraction (PVC) identification, and tachograms. …”
Get full text

A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology: a cohort study by Jinsong Du, Jinsong Du, Jinsong Du, Xinru Tao, Le Zhu, Wenhao Qi, Xiaoqiang Min, Xiaoqiang Min, Hongyan Deng, Shujie Wei, Xiaoyan Zhang, Xiao Chang

“…By enabling early depression detection and evidence-based interventions for middle-aged and older adult populations, it establishes a novel health management paradigm with demonstrated potential to improve quality of life.…”
Get full text

Application of precision agriculture technologies for crop protection and soil health by Emogine Mamabolo, Makgabo Johanna Mashala, Ephias Mugari, Tlou Elizabeth Mogale, Norman Mathebula, Kabisheng Mabitsela, Kwabena Kingsley Ayisi

“…Among the technologies, spectral imaging emerged as the most widely used for early detection of plant stress, diseases, and pests, followed by machine learning algorithms, UAVs (Unmanned Aerial Vehicles), and IoT (Internet of Things) devices, all of which enable real-time monitoring and targeted interventions. …”
Get full text

HI4HC and AAAAD: Exploring a hierarchical method and dataset using hybrid intelligence for remote sensing scene captioning by Jiaxin Ren, Wanzeng Liu, Jun Chen, Shunxi Yin

“…To address these shortcomings, we propose HI4HC (hybrid intelligence for remote sensing scene hierarchical captioning), a novel method that combines deep learning algorithms with expert knowledge to generate hierarchical captions for remote sensing scenes. …”
Get full text

Recovering Pulsar Periodicity from Time-of-arrival Data by Finding the Shortest Vector in a Lattice by Dotan Gazith, Aaron B. Pearlman, Barak Zackay

“…Identifying such a periodicity from a discrete set of arrival times is a difficult algorithmic problem, In particular when the pulsar is in a binary system. …”
Get full text

Towards consistently measuring and monitoring habitat condition with airborne laser scanning and unmanned aerial vehicles by W. Daniel Kissling, Yifang Shi, Jinhu Wang, Agata Walicka, Charles George, Jesper E. Moeslund, France Gerard

“…A VRE would also improve data management, metadata standardization, workflow reproducibility, and transferability of structure-from-motion algorithms and machine learning models such as random forests and convolutional neural networks. …”
Get full text

Multimodal approaches and AI-driven innovations in dementia diagnosis: a systematic review by Revati M. Wahul, Sarita Ambadekar, Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Manisha A. Dudhedia, Varsha Gaikwad, Bhavana Kanawade, J. R. Pansare, Balaji Bodkhe, S. H. Gawande

“…This survey will compare the study’s algorithms or frameworks on sensitivity, specificity, interpretability, computational efficiency, and clinical transnationality concerning early detection and monitoring progression. …”
Get full text

Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…To ensure reliability, robust data preprocessing was conducted using the Monte Carlo outlier detection (MCOD) method to recognize and manage data outliers. …”
Get full text

The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

“…As revealed by RF, the importance of features indicates that all feature modalities (HRV, SpO2, and anthropometric variables) contribute to the top 10 ranks.ConclusionThe present study demonstrates the feasibility of using classification models to detect the presence and severity of OSA using these indices. …”
Get full text

Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies by Yero S. Ndiaye, Yero S. Ndiaye, Peter Cramton, Peter Cramton, Chavdar Chernev, Chavdar Chernev, Axel Ockenfels, Axel Ockenfels, Tobias Schwarz

“…The AI software used a deep-learning algorithm and returned a coded abnormal or normal diagnosis for each finding in the study. …”
Get full text

A Robust Behavioral Biometrics Framework for Smartphone Authentication via Hybrid Machine Learning and TOPSIS by Moceheb Lazam Shuwandy, Qutaiba Alasad, Maytham M. Hammood, Ayad A. Yass, Salwa Khalid Abdulateef, Rawan A. Alsharida, Sahar Lazim Qaddoori, Saadi Hamad Thalij, Maath Frman, Abdulsalam Hamid Kutaibani, Noor S. Abd

“…Our analysis, supported by experimental results, ensure that the RF model outperforms the two other ML algorithms by getting F1-Score, accuracy, recall, and precision of 95.1%, 95.2%, 95.5%, and 94.8%, respectively. …”
Get full text

Statistical Characteristics of Nighttime Medium‐Scale Traveling Ionospheric Disturbances From 10‐Years of Airglow Observation by the Machine Learning Method by Chang Lai, Jiyao Xu, Zhishuang Lin, Kun Wu, Donghe Zhang, Qinzeng Li, Longchang Sun, Wei Yuan, Yajun Zhu

“…The classification model and detection model have accuracies of 96.9% and 70%–85%, respectively. …”
Get full text

A Novel SOH Estimation Method for Lithium-Ion Batteries Based on the PSO–GWO–LSSVM Prediction Model with Multi-Dimensional Health Features Extraction by Xu He, Zhengpu Wu, Jinghan Bai, Junchao Zhu, Lu Lv, Lujun Wang

“…To improve LSSVM model accuracy and efficiency, this paper develops a novel prediction model that uses particle swarm optimization (PSO) combined with grey wolf optimization (GWO) algorithms to optimize the LSSVM model. The generalization performance of the proposed method is validated through comparative experiments using a battery dataset provided by the Center for Advanced Life Cycle Engineering (CALCE) Research Center at the University of Maryland. …”
Get full text

Analysis of types of medical interventions for patients with pancreatic adenocarcinoma in hospitals of Saint Petersburg for the period from 2014 to 2020 by V. E. Moiseenko, A. V. Pavlovsky, D. A. Granov, L. V. Kochorova, N. I. Vishnjakov, V. V. Hizha, A. V. Yazenok, N. Ju. Shirshova, L. A. Solovyova

“…The data obtained from such an analysis can become the basis for the development of algorithms and programs for optimizing the provision of care for patients suffering from this pathology. …”
Get full text

Ethical Foundations of AI-Driven Avatars in the Metaverse for Innovation and User Privacy by Ammar Almomani, Ahmad Al-Qerem, Mohammad Alauthman, Amjad Aldweesh, Samer Aoudi, Said A. Salloum

“…However, these advances also introduce critical ethical and legal dilemmas surrounding privacy, identity theft, algorithmic bias, and data governance. This study employs a comprehensive multimethodological approach combining systematic literature review, regulatory gap analysis, and ethical framework synthesis. …”
Get full text

Prediction of black soldier fly larval sex and morphological traits using computer vision and deep learning by Sarah Nawoya, Quentin Geissmann, Henrik Karstoft, Kim Bjerge, Roseline Akol, Andrew Katumba, Cosmas Mwikirize, Grum Gebreyesus

“…The study explores algorithms utilizing You-Only-Look-Once (YOLOv8) in detection and segmentation, ResNet for feature extraction and classification, and regression analysis mechanisms. …”
Get full text

Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes by Jiaying Ge, Siqi Sun, Jiangping Zeng, Yujie Jing, Huihui Ma, Chunhua Qian, Ran Cui, Shen Qu, Hui Sheng

“…Predictive models were developed using logistic regression, random forest, and other algorithms, with feature selection via LASSO regression. …”
Get full text

Proteomic analysis of blood plasma as a tool for personalized diagnosis of lung adenocarcinoma by D. N. Korobkov, A. S. Kononikhin, S. D. Semenov, H. L. Kordzaya, A. G. Brzhozovskiy, A. E. Bugrova, E. Yu. Vasilieva, D. Yu. Kanner, E. N. Nikolaev, A. A. Komissarov

“…The data obtained were analyzed using modern methods of biological statistics, including machine learning algorithms.Results. Based on the quantitative analysis of 118 proteins in blood plasma between the experimental groups, we proposed a panel of 12 significant proteins that are specific markers of LAC. …”
Get full text

Region-wise landmarks-based feature extraction employing SIFT, SURF, and ORB feature descriptors to recognize Monozygotic twins from 2D/3D Facial Images [version 2; peer review: 2... by Srikanth Prabhu, Vinod Nayak, Aparna Jayakala, Krishna Prakasha K, Gangothri Sanil

“…It is one of the desired detection techniques employed in forensics for criminal identification. …”
Get full text

Insights from UKCTOCS for design, conduct and analyses of large randomised controlled trials by Usha Menon, Aleksandra Gentry-Maharaj, Matthew Burnell, Sophia Apostolidou, Andy Ryan, Jatinderpal K Kalsi, Naveena Singh, Lesley Fallowfield, Alistair J McGuire, Stuart Campbell, Steven J Skates, Anne Dawnay, Mahesh Parmar, Ian J Jacobs

“…We feel that our solutions are highly relevant, especially as there is a renewed focus on trials for early detection of cancer.…”
Get full text