Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite by Imane Khalil, Amina Daghouri, Mohammed Alae Chanoui, Zouhair Guennoun, Adnane Addaim

“…Deep learning has been increasingly utilized for cloud detection in Earth observation nanosatellites, offering effective solutions to enhance mission performance. …”
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Optimizing Stroke Classification with Pre-Trained Deep Learning Models by Serra Aksoy, Pinar Demircioglu, Ismail Bogrekci

“…This study aims to investigate the use of deep learning techniques for predicting ischemic strokes with high accuracy, enabling earlier diagnosis and intervention. …”
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Untangling profiles of postthrombotic syndrome using unsupervised machine learning by Aaron F. J. Iding, Vincent ten Cate, Hugo ten Cate, Philipp S. Wild, Arina J. ten Cate-Hoek

“…This study applied unsupervised machine learning to investigate the heterogeneity of PTS among patients and within the Villalta scale. …”
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Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

“…However, no predictive models for BSH have been developed using machine learning algorithms.<h4>Objective</h4>To evaluate the effectiveness of five machine learning algorithms in predicting thickening of the basal segment of the interventricular septum and to develop a simple, yet efficient, prediction model for BSH.…”
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Snoring Sound Recognition Using Multi-Channel Spectrograms by Ziqiang YE, Jianxin PENG, Xiaowen ZHANG, Lijuan SONG

“…Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a common and high-risk sleep-related breathing disorder. …”
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A machine learning framework for predicting healthcare utilization and risk factors by Yead Rahman, Prerna Dua

“…This study analyzes over 6.3 million records from the Louisiana Department of Health (LDH) to identify the most effective machine learning models for predicting clinical service utilization, COVID-19 infections, and tobacco use. …”
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Improving Sleep Disorder Diagnosis Through Optimized Machine Learning Approaches by Md. Atiqur Rahman, Israt Jahan, Maheen Islam, Taskeed Jabid, Md Sawkat Ali, Mohammad Rifat Ahmmad Rashid, Mohammad Manzurul Islam, Md. Hasanul Ferdaus, Md Mostofa Kamal Rasel, Mahmuda Rawnak Jahan, Shayla Sharmin, Tanzina Afroz Rimi, Atia Sanjida Talukder, Md. Mafiul Hasan Matin, M. Ameer Ali

“…Classifying sleep disorders, such as obstructive sleep apnea and insomnia, is crucial for improving human quality of life due to their significant impact on health. …”
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Construction and analysis of corporate greenwashing index: a deep learning approach by Xiao Wang, Xukuo Gao, Meng Sun

“…A corporate greenwashing index is constructed using the deep learning-based MacBERT model, which demonstrates bidirectional processing capabilities. …”
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Norm-Based Outlier Filtering and Consensus Aggregation for Robust Federated Learning by Hasung Yeo, Joon-Woo Lee

“…Federated Learning (FL) enables collaborative training of machine learning models across distributed clients without sharing private data, making it ideal for privacy-sensitive applications. …”
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COVID-19 AND COLORECTAL SURGERY: LESSONS LEARNED FROM FIRST CASES by İlker Özgür, İrem Karataş, Leman Damla Ercan, Ali Fuat Kaan Gök, Alpay Medetalibeyoğlu, Murat Köse, Mehmet Türker Bulut, Metin Keskin

“…It became complicated to manage surgical complications such as stoma complication, surgical site infection, and small bowel obstruction. Nonetheless, while patients with underlying health conditions have a high mortality rate from COVID-19 infection, no death was observed in this small case series. …”
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Highlights del 57.° Congreso de la Sociedad Española de Neumología y Cirugía Torácica (SEPAR) by Amaya Martínez Meñaca, Marta García Moyano, Pablo Sánchez-Salcedo, Juan Cascón-Hernández, Nicola Sante Diciolla, Mariana Muñoz-Ezquerre, Esther Barbero Herranz, Tamara Alonso Pérez

“…The SEPAR Congress is the leading meeting for the entire respiratory scientific community, which allows learning about the main scientific advances in this area and provides the ideal situation to create and strengthen ties. …”
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A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation by Or Inbar, Omri Inbar, Ronen Reuveny, Michael J. Segel, Hayit Greenspan, Mickey Scheinowitz

“…Of the 234 CPETs, 150 (50 in each group) tests were used for the support vector machine (SVM) learning stage, and the remaining 84 tests were used for the model validation. …”
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Predicting postoperative pulmonary infection risk in patients with diabetes using machine learning by Chunxiu Zhao, Bingbing Xiang, Jie Zhang, Pingliang Yang, Qiaoli Liu, Shun Wang

“…Predictive models were constructed using nine different machine learning algorithms. Feature selection was conducted using Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression. …”
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Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms by Haobo Kong, Yong Li, Ya Shen, Jingjing Pan, Min Liang, Zhi Geng, Yanbei Zhang

“…Abstract Background This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms. Methods Data were collected from two centers and categorized into development and validation cohorts. …”
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Deep learning based automation of mean linear intercept quantification in COPD research by Lars Leyendecker, Anna Louisa Weltin, Florian Nienhaus, Michaela Matthey, Bastian Nießing, Daniela Wenzel, Daniela Wenzel, Robert H. Schmitt, Robert H. Schmitt

“…Chronic obstructive pulmonary disease (COPD), a major cause of global mortality, necessitates novel therapies targeting lung function and remodeling. …”
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Non-line-of-sight Visible Light Positioning System based on Deep Learning by HUANG Weijie, LIN Bangjiang, DING Yongqi, LUO Jiabin, HUANG Tianming

“…However, traditional VLP systems rely on Line-of-Sight (LOS) paths and cannot function properly when obstructed by obstacles.【Methods】To address this issue, we propose a novel Non-Line-of-Sight (NLOS) VLP system based on deep learning. …”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…In the case where the target is obstructed, the tracking accuracy of the raised method is as high as 0.95. …”
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Challenges in machine learning-based social bot detection: a systematic review by Nasser Alkathiri, Khaled Slhoub

“…This systematic literature review aims to identify, categorize, and analyze the key challenges obstructing the advancement of machine learning-based social bot detection systems while consolidating existing strategies proposed in the literature to address these obstacles. …”
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Improving Railway Track Detection With a Mixed-Modality Deep Learning Approach by Wichian Ooppakaew, Jakkrit Onshaunjit, Saifun Khrueakhrai, Jakkree Srinonchat

“…The present study introduces a sophisticated railway track identification system that utilizes semantic segmentation methods and deep learning models to effectively distinguish between items and persons in close proximity to railway zones. …”
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Personalized decision making for coronary artery disease treatment using offline reinforcement learning by Peyman Ghasemi, Matthew Greenberg, Danielle A. Southern, Bing Li, James A. White, Joon Lee

“…We applied off-policy reinforcement learning (RL) to a composite data model from 41,328 unique patients with angiography-confirmed obstructive CAD. …”
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