A machine learning–based risk prediction model for atrial fibrillation in critically ill patients by Laith Alomari, MD, Yaman Jarrar, MD, Zaid Al-Fakhouri, MD, Emmanuel Otabor, MBBS, Justin Lam, MD, Jana Alomari

“…Objective: This study developed a machine learning–based model to enable early AF risk identification and prevention. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…However, with the advancement of industrial technology, the prevalence of surface defects in particleboard is decreasing, making the acquisition of sample data difficult and significantly limiting the effectiveness of model training. Deep reinforcement learning-based detection methods have been shown to exhibit strong generalization ability and sample utilization efficiency when the number of samples is limited. …”
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Wearable sensor-based fall detection for elderly care using ensemble machine learning techniques by Ch Gangadhar, P Pavithra Roy, R. Dinesh Kumar, Janjhyam Venkata Naga Ramesh, S. Ravikanth, N. Akhila

“…Each module in the unique category-based composite structure is recognized at a certain level. …”
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AI-Enhanced Photovoltaic Power Prediction Under Cross-Continental Dust Events and Air Composition Variability in the Mediterranean Region by Pavlos Nikolaidis

“…Using machine learning methods, particularly regression trees, the proposed approach evaluates the impact of key environmental variables on PV performance, with an emphasis on atmospheric dust transport and air composition variability. …”
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IsoFoodTrack: a comprehensive database and management system based on stable isotope ratio analysis for combating food fraud by Cathrine Terro, Cathrine Terro, Robert Modic, Matevž Ogrinc, Andraž Simčič, Jan Drole, Tome Eftimov, Tome Eftimov, Barbara Koroušić Seljak, Barbara Koroušić Seljak, Nives Ogrinc, Nives Ogrinc

“…Based on the data collected in IsoFoodTrack using statistical, chemometric and machine learning approaches it has a capability to identify and classify the origin of food commodities. …”
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Video Interpolation-Based Multi-Source Data Fusion Method for Laser Processing Melt Pool by Hang Ren, Yuhui Zhang, Huaping Li, Yu Long

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Satellite-Derived Bathymetry Using Sentinel-2 and Airborne Hyperspectral Data: A Deep Learning Approach with Adaptive Interpolation by Seung-Jun Lee, Han-Saem Kim, Hong-Sik Yun, Sang-Hoon Lee

“…This study presents a deep learning-based approach that fuses Sentinel-2 multispectral imagery with airborne hyperspectral-derived reference data to generate high-resolution satellite-derived bathymetry (SDB). …”
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Integrating geostatistical methods and deep learning for enhanced 87Sr/86Sr isoscape Estimation: A case study in South Korea by Hyeongmok Lee, Go-Eun Kim, Woo-Jin Shin, Yuyoung Lee, Sanghee Park, Kwang-Sik Lee, Jina Jeong, Seung-Ik Park, Sungwook Choung

“…To address this, we propose a hybrid framework for 87Sr/86Sr isoscape mapping that integrates a kriging-based data augmentation method with a deep learning (DL) classifier. …”
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Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale E... by Nanxiang Zhang, Qi Pan, Shuo Yang, Leen Huang, Jianan Yin, Hai Lin, Xiang Huang, Chonglong Ding, Xinyan Zou, Yongjun Zheng, Jinxin Zhang

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Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study by Nai-Yu Kuo, Hsin-Jung Tsai, Shih-Jen Tsai, Albert C Yang

“…ObjectiveThis study aims to develop 2 sequential machine learning models to efficiently screen and differentiate OSA. …”
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Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state by Aydin Larestani, Sara Sahebalzamani, Abdolhossein Hemmati-Sarapardeh, Ali Naseri

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Predicting viral proteins that evade the innate immune system: a machine learning-based immunoinformatics tool by Jorge F. Beltrán, Lisandra Herrera Belén, Alejandro J. Yáñez, Luis Jimenez

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Image-Based Nutritional Advisory System: Employing Multimodal Deep Learning for Food Classification and Nutritional Analysis by Sheng-Tzong Cheng, Ya-Jin Lyu, Ching Teng

“…This study proposes an image-based nutritional advisory system that integrates multimodal deep learning to automate food classification, volume estimation, and dietary recommendation to address these limitations. …”
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A Deep Learning-Based Solution to the Class Imbalance Problem in High-Resolution Land Cover Classification by Pengdi Chen, Yong Liu, Yuanrui Ren, Baoan Zhang, Yuan Zhao

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Automatic Analysis of Ultrasound Images to Estimate Subcutaneous and Visceral Fat and Muscle Tissue in Patients with Suspected Malnutrition by Antonio Cuesta-Vargas, José María Arjona-Caballero, Gabriel Olveira, Daniel de Luis Román, Diego Bellido-Guerrero, Jose Manuel García-Almeida

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Quantifying synthetic bacterial community composition with flow cytometry: efficacy in mock communities and challenges in co-cultures by Fabian Mermans, Ioanna Chatzigiannidou, Wim Teughels, Nico Boon

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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

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Machine learning metallic glass critical cooling rates through elemental and molecular simulation based featurization by Lane E. Schultz, Benjamin Afflerbach, Paul M. Voyles, Dane Morgan

“…We have developed a machine learning model for critical cooling rates for metallic glasses based on computational properties, supporting in-silico screening for desired Rc values and significantly reducing reliance on time-consuming laboratory work. …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…In this study, we develop a novel ML-based method to quantify thousands of CAR cell IS images with enhanced accuracy and speed. …”
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A novel framework to identify delamination location/size in BFRP pipe based on convolutional neural network (CNN) algorithm hybrid with capacitive sensors by Wael A. Altabey

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