Exploring the link between the ZJU index and sarcopenia in adults aged 20–59 using NHANES and machine learning by Huan Chen, Ning Du, Hong Xiao, Zhao Wang

“…Abstract Sarcopenia, characterized by progressive loss of muscle mass and function, is a growing public health concern. The ZJU index, a novel metabolic marker, integrates lipid metabolism and glucose regulation parameters. …”
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Automated Detection of Micro-Scale Porosity Defects in Reflective Metal Parts via Deep Learning and Polarization Imaging by Haozhe Li, Xing Peng, Bo Wang, Feng Shi, Yu Xia, Shucheng Li, Chong Shan, Shiqing Li

“…This framework introduces the SNWD (Selective Network with attention for Defect and Weathering Degradation) Loss function, which combines the SIOU Angle Loss with the NWD distribution sensing characteristics. …”
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Security of End-to-End medical images encryption system using trained deep learning encryption and decryption network by Saba Inam, Shamsa Kanwal, Anousha Anwar, Noor Fatima Mirza, Hessa Alfraihi

“…Specifically, the Cycle_GAN network is used as the leading learning network. This work suggests deep learning-based encryption for medical images using Cycle_GAN, a Generative Adversarial Network. …”
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Machine Learning-Based VO₂ Estimation Using a Wearable Multiwavelength Photoplethysmography Device by Chin-To Hsiao, Carl Tong, Gerard L. Coté

“…This study presents a novel wrist-worn multiwavelength photoplethysmography (PPG) device and machine learning algorithm designed to estimate VO₂ continuously. …”
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CGD-CD: A Contrastive Learning-Guided Graph Diffusion Model for Change Detection in Remote Sensing Images by Yang Shang, Zicheng Lei, Keming Chen, Qianqian Li, Xinyu Zhao

“…The network is trained with a carefully crafted contrastive loss function to effectively capture high-level structural information. …”
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Design a path – planning strategy for mobile robot in multi-structured environment based on distributional reinforcement learning by Anh-Tu Nguyen, Duc-Duy Pham, Van-Nghia Le, Vu-Hai Luu

“…The image data before and after denoising processes, as well as the values of the reward function, are analyzed across various environmental scenarios to evaluate the effectiveness of this framework. …”
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Two-Stream Modality-Based Deep Learning Approach for Enhanced Two-Person Human Interaction Recognition in Videos by Hemel Sharker Akash, Md Abdur Rahim, Abu Saleh Musa Miah, Hyoun-Sup Lee, Si-Woong Jang, Jungpil Shin

“…Moreover, we newly created a custom filter function to enhance computational efficiency and eliminate irrelevant keypoints and mesh components from the dataset. …”
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Photomediated ion dynamics enables multi-modal learning, memory and sensing in ultralow-voltage organic electrochemical device by Guocai Liu, Wei Wen, Cong Shan, Haojie Huang, Yao Zhao, Yangshuang Bian, Yunlong Guo, Hui Huang, Yunqi Liu

“…Abstract Ion signaling enables biological systems to implement learning, memory and sensing tasks in an energy-efficient manner. …”
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Early detection of positive urine culture in patients with urolithiasis: a machine learning model with dynamic online nomogram by Di Luo, Jingdong Zhang, Linguo Xie, Chunyu Liu, Rui Wang

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Exploring the role of lipid metabolism related genes and immune microenvironment in periodontitis by integrating machine learning and bioinformatics analysis by Lulu Wei, Miaomiao Chen, Xin Shi, Yibing Wang, Shengwei Yang

“…Differential expression analysis identified differentially expressed LMRGs (DELMRGs), followed by functional enrichment analyses to elucidate their biological functions. …”
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A development of machine learning models to preoperatively predict insufficient clinical improvement after total knee arthroplasty by Geunwu Gimm, Byoungjun Jeon, Sung Eun Kim, Byeong Soo Kim, Hyuk-Soo Han, Sungwan Kim

“…This study aimed to develop and validate machine learning (ML) models that preoperatively predict insufficient clinical improvement one year after TKA using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscales and total scores, and to assess the important predictive variables. …”
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Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases by Miad Boodaghidizaji, Thaisa Jungles, Tingting Chen, Bin Zhang, Tianming Yao, Alan Landay, Ali Keshavarzian, Bruce Hamaker, Arezoo Ardekani

“…Abstract Gut microbiota has been implicated in the pathogenesis of multiple gastrointestinal (GI) and systemic metabolic and inflammatory disorders where disrupted gut microbiota composition and function (dysbiosis) has been found in multiple studies. …”
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Fresh Tea Leaf-Grading Detection: An Improved YOLOv8 Neural Network Model Utilizing Deep Learning by Zejun Wang, Yuxin Xia, Houqiao Wang, Xiaohui Liu, Raoqiong Che, Xiaoxue Guo, Hongxu Li, Shihao Zhang, Baijuan Wang

“…Additionally, the substitution of the loss function with SIoU facilitates a more rapid model convergence and a more precise pinpointing of defect locations. …”
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Risk Factors and Comorbidities Associated to Cardiovascular Disease in Qatar: A Machine Learning Based Case-Control Study by Hamada R. H. Al-Absi, Mahmoud Ahmed Refaee, Atiq Ur Rehman, Mohammad Tariqul Islam, Samir Brahim Belhaouari, Tanvir Alam

“…The objective of this case-control study was to develop machine learning (ML) model distinguishing healthy individuals from people having CVD, which could ultimately reveal the list of potential risk factors associated to CVD in Qatar. …”
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Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning by Jiao Qiu, Yalin Xu, Luyuan Tong, Xingchun Yang, Xiao Wu

“…Differential expression gene analysis (DEGs) and weighted gene co-expression network analysis (WGCNA) were carried out to identify the RA-RF-DEGs. Subsequently, functional enrichment analysis was performed to clarify the biological functions of these genes. …”
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Beyond motor learning: Insights from infant magnetic resonance imaging on the critical role of the cerebellum in behavioral development by Lauren Wagner, Melis E Cakar, Megan Banchik, Emily Chiem, Siobhan Sive Glynn, Amy H Than, Shulamite A Green, Mirella Dapretto

“…Although the cerebellum is now recognized for its crucial role in non-motor functions such as language, perceptual processes, social communication, and executive function in adults, it is often overlooked in studies of non-motor behavioral development in infancy. …”
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Machine learning-based identification of histone deacetylase-associated prognostic factors and prognostic modeling for low-grade glioma by Keshan Wen, Weijie Zhu, Ziyi Luo, Wei Wang

“…Abstract Background Low-grade glioma (LGG) is a slow-growing but invasive tumor that affects brain function. Histone deacetylases (HDACs) play a critical role in gene regulation and tumor progression. …”
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Pilot Study of Using Machine Learning to Detect Atherosclerotic Renal Artery Stenosis From Spectral Doppler Waveforms by Haseeb Mukhtar, Seyed Moein Rassoulinejad-Mousavi, Shahriar Faghani, Bradley J. Erickson, Sanjay Misra

“…An Adam optimizer with a learning rate of 0.001 and a cross-entropy loss function were utilized. …”
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Robust Semantic Segmentation of Wafer Transmission Electron Microscopy Image Using Multi-Task Learning With Edge Detection by Yongwon Jo, Jinsoo Bae, Hansam Cho, Sungsu Kim, Heejoong Roh, Kyunghye Kim, Munki Jo, Munuk Kim, Jaeung Tae, Seoung Bum Kim

“…Our approach includes three primary components: a pre-training phase using self-supervised representation learning to extract meaningful representations from unlabeled wafer TEM images, a multi-task learning-based fine-tuning phase incorporating both semantic segmentation and edge detection tasks, and a boundary-aware loss function to enhance boundary recognition accuracy. …”
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Empowering Security Operation Center With Artificial Intelligence and Machine Learning—A Systematic Literature Review by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…Finally, a case study is presented to describe the function of ML- and AI-powered SOC components to achieve optimum security. …”
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