Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma by Songyun Zhao, Zihao Li, Kaibo Liu, Gaoyi Wang, Quanqiang Wang, Hua Yu, Wanying Chen, Hao Dai, Yijun Li, Jiaheng Xie, Yucang He, Liqun Li

“…Methods We obtained and processed transcriptomic data, including RNA expression profiles, methylation microarray data, gene mutation data, and clinical information, from the TCGA dataset using multi-omics analysis and machine learning techniques. …”
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4 Pattern Recognition for Healing Burns to Compute Evidence: Space Syntax and Machine Learning Analysis of Burns Center Karachi by Javaria Manzoor Shaikh, JaeSeung Park

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Protection Analysis of a Traveling-Wave, Machine-Learning Protection Scheme for Distributions Systems With Variable Penetration of Solar PV by Miguel Jimenez-Aparicio, Trupal R. Patel, Matthew J. Reno, Javier Hernandez-Alvidrez

“…This work provides a detailed protection analysis of a fast, Traveling-Wave (TW), Machine-Learning (ML), local, non-directional, economic, and setting-less protection scheme. …”
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Integrating machine learning and reliability analysis: A novel approach to predicting heavy metal removal efficiency using biochar by Mohammad Sadegh Barkhordari, Chongchong Qi

“…The framework addresses key challenges by employing data imputation to manage missing information, data augmentation to overcome limitations of small datasets, and reliability analysis to assess predictive uncertainties, thereby improving the model’s reliability and generalization capability. …”
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A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease by Arshpreet Singh Badesha, Russell Frood, Marc A. Bailey, Patrick M. Coughlin, Andrew F. Scarsbrook

“…Radiomics involves the extraction of quantitative data from imaging features that are imperceptible to the eye. …”
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ANALYSIS OF REAL RELATIVE ASYMMETRY IN URBAN TRANSPORTATION NETWORK PROBLEMS USING SPACE SYNTAX, REDS, AND MACHINE LEARNING CONCEPTS by Robiatul Adawiyah, Fitriyatul Mardiyah, Dafik Dafik, Ika Hesti Agustin, Excelsa Suli Wildhatul Jannah, Marsidi Marsidi

“…The novelty of this research lies in the integration of spatial configuration analysis, graph theoretical optimization, and machine learning-based forecasting, offering a comprehensive approach not previously combined in related studies. …”
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Socializing AI: Integrating Social Network Analysis and Deep Learning for Precision Dairy Cow Monitoring—A Critical Review by Sibi Chakravathy Parivendan, Kashfia Sailunaz, Suresh Neethirajan

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Urban Tree Canopy Mapping and Analysis Using Iterative Annotation Method and Deep Learning: A Case Study in Beijing by Yulong Ding, Ximin Cui, Zhengchao Chen, Zeqing Wang, Debao Yuan, Xiang Meng, Xuan Yang, Yue Xu, Xiangyu Tian

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ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis by Weihong Huang, Wudi Wei, Xiaotao He, Baili Zhan, Xiaoting Xie, Meng Zhang, Shiyi Lai, Zongxiang Yuan, Jingzhen Lai, Rongfeng Chen, Junjun Jiang, Li Ye, Hao Liang

“…In total, 5 deep learning architectures—long short-term memory (LSTM), neural basis expansion analysis for time series (N-BEATS), transformer, temporal fusion transformer (TFT), and time-series dense encoder (TiDE)—were developed using a ChatGPT-assisted workflow covering code generation, error debugging, and performance optimization. …”
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Analysis of aPTT predictors after unfractionated heparin administration in intensive care units using machine learning models. by Tadashi Kamio, Masaru Ikegami, Megumi Mizuno, Seiichiro Ishii, Hayato Tajima, Yoshihito Machida, Kiyomitsu Fukaguchi

“…<h4>Methods</h4>Data were obtained from the Tokushukai Medical Database, covering six hospitals with ICUs in Japan, collected between 2018 and 2022. …”
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Performance Efficiency Improvement of Parabolic Solar Concentrating Collector (An Experimental Evaluation and Analysis) by Durai Kumar

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Revolutionizing diagnosis of pulmonary Mycobacterium tuberculosis based on CT: a systematic review of imaging analysis through deep learning by Fei Zhang, Hui Han, Minglin Li, Tian Tian, Guilei Zhang, Zhenrong Yang, Feng Guo, Maomao Li, Yuting Wang, Jiahe Wang, Ying Liu

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Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis by Jong-Ho Kim, Hye-Sook Kim, Jong-Hee Sohn, Sung-Mi Hwang, Jae-Jun Lee, Young-Suk Kwon

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Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning by Li Xie, Han Xiao, Maoyu Zhao, Li Xu, Si Tang, Youzhu Qiu

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Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells by Tian Xu, Qin Xu, Ran Lu, David N. Oakland, Song Li, Liwu Li, Christopher M. Reilly, Xin M. Luo

“…Conventional machine learning approaches such as principal component analysis have been employed in single-cell RNA sequencing (scRNA-seq) analysis to characterize DNT cells. …”
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Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis by Xiangui Lv, Daiqiang Liu, Xinwei Chen, Lvlin Chen, Xiaohui Wang, Xiaomei Xu, Lin Chen, Chao Huang

“…Abstract Background Predicting mortality in sepsis-related acute kidney injury facilitates early data-driven treatment decisions. Machine learning is predicting mortality in S-AKI in a growing number of studies. …”
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Enhanced Conditional GAN for High-Quality Synthetic Tabular Data Generation in Mobile-Based Cardiovascular Healthcare by Malak Alqulaity, Po Yang

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Anomaly Detection Utilizing One-Class Classification—A Machine Learning Approach for the Analysis of Plant Fast Fluorescence Kinetics by Nam Trung Tran

“…The results highlight the still largely unexploited potential of Machine Learning in OJIP analysis.…”
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Development of Machine Learning–Based Risk Prediction Models to Predict Rapid Weight Gain in Infants: Analysis of Seven Cohorts by Miaobing Zheng, Yuxin Zhang, Rachel A Laws, Peter Vuillermin, Jodie Dodd, Li Ming Wen, Louise A Baur, Rachael Taylor, Rebecca Byrne, Anne-Louise Ponsonby, Kylie D Hesketh

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Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems by Gusev Pavel, Tavolzhanskij Alexander, Zolnikov Vladimir, Deniskina Antonina

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