Rates of lobar atrophy in asymptomatic MAPT mutation carriers by Qin Chen, Bradley F. Boeve, Matthew Senjem, Nirubol Tosakulwong, Timothy G. Lesnick, Danielle Brushaber, Christina Dheel, Julie Fields, Leah Forsberg, Ralitza Gavrilova, Debra Gearhart, Jonathan Graff‐Radford, Neill R. Graff‐Radford, Clifford R. Jack Jr., David T. Jones, David S. Knopman, Walter K. Kremers, Maria Lapid, Rosa Rademakers, Jeremy Syrjanen, Adam L. Boxer, Howie Rosen, Zbigniew K. Wszolek, Kejal Kantarci, LEFFTDS Consortium

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Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study by Wei Jiang, Yaosheng Zhang, Jiayi Weng, Lin Song, Siqi Liu, Xianghui Li, Shiqi Xu, Keran Shi, Luanluan Li, Chuanqing Zhang, Jing Wang, Quan Yuan, Yongwei Zhang, Jun Shao, Jiangquan Yu, Ruiqiang Zheng

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Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells by Tianxiang Zhang, Chunhui Yuan, Mo Chen, Jinjiang Liu, Wei Shao, Ning Cheng

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Ferroptosis-related hub genes and immune cell dynamics as diagnostic biomarkers in age-related macular degeneration by Jinquan Chen, Zhao Long, Dandan Shi, Qian Zhang, H. Peng

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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

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Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study by Jin-Hyun Park, Inyong Jeong, Gang-Jee Ko, Seogsong Jeong, Hwamin Lee

“…Five machine learning algorithms were compared, and the best-performing model was selected based on the area under the receiver operating characteristic curve. …”
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Advanced prediction of rice yield gaps under climate uncertainty using machine learning techniques in Eastern India by Satiprasad Sahoo, Chiranjit Singha, Ajit Govind

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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…ConclusionsThis study evaluates prediction models constructed using various ML algorithms, with results showing that ML demonstrates high performance in ARDS prediction. …”
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Cutting through the noise: A Three-Way Comparison of Median, Adaptive Median, and Non-Local Means Filter for MRI Images by Raniya Ashraf, Roz Nisha, Fahad Shamim, Sarmad Shams

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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

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CPAP management of COVID-19 respiratory failure: a first quantitative analysis from an inpatient service evaluation by Abdul Ashish, Alison Unsworth, Jane Martindale, Kanishka Kavuri, Luigi Sedda, Martin Farrier

“…This evaluation should stimulate further research questions and larger study designs on the potential benefit of CPAP for COVID-19 infections. …”
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The TOMMORROW study: Design of an Alzheimer's disease delay‐of‐onset clinical trial by Daniel K. Burns, Carl Chiang, Kathleen A. Welsh‐Bohmer, Stephen K. Brannan, Meredith Culp, Janet O'Neil, Grant Runyan, Patrick Harrigan, Brenda L. Plassman, Michael Lutz, Eric Lai, Stephen Haneline, David Yarnall, Deborah Yarbrough, Craig Metz, Sridevi Ponduru, Scott Sundseth, Ann M. Saunders, TOMMORROW Study Investigators

“…Abstract Introduction Alzheimer's disease (AD) is a continuum with neuropathologies manifesting years before clinical symptoms; thus, AD research is attempting to identify more disease‐modifying approaches to test treatments administered before full disease expression. …”
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Flexible Dirichlet Mixture Model for Multi-modal data Clustering by Seunghyun Hong, Fatma Najar, Manar Amayri, Nizar Bouguila

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House Price Prediction of Real Time Data (DHA Defence) Karachi Using Machine Learning by Lata Bai Gokalani, Bhagwan Das, Dilip Kumar Ramnani, Mahender Kumar, Mazhar Ali Shah

“…It is one of the main contribution of the work is that through this the house prediction model based on DHA Karachi data is developed and as per best of our knowledge till today there is no prediction of housing for the country’s important has been developed. has This research paper mainly focuses on real time Defense Housing Authority (DHA) Karachi data, applying different regression algorithms like Decision tree, Random forest and linear regression to find the sales price prediction of the house and compare the performance of these models. …”
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Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models by xuanbo su, Nizar Bouguila, Nuha Zamzami

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Knowledge-infused and Explainable Malware Forensics by Neha Mohan Kumar, Sheikh Rabiul Islam

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Choosing the Right Metrics: A Study of Performance Measurement for Binary Classification in Imbalanced and Big Data by Mary Anne Walauskis, Taghi M. Khoshgoftaar

“…We analyzed 23 publicly available datasets from diverse domains, ranging in size from 309 to over five million instances and distribution levels from 0.17% to 44.87%, using two gradient boosting algorithms, LightGBM and XGBoost, and one unsupervised anomaly detection algorithm, Isolation Forest. …”
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What happens between first symptoms and first acute exacerbation of COPD – observational study of routine data and patient survey by Alex Bottle, Alex Adamson, Xiubin Zhang, Benedict Hayhoe, Jennifer K Quint

“…Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/99/72) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 43. …”
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Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program by Samuel Dagogo-Jack, Søren Brunak, Carlos Lorenzo, Kieren J Mather, Marinella Temprosa, Tibor V Varga, Jinxi Liu, Ronald B Goldberg, Guannan Chen, Xavier Pi-Sunyer

“…Machine learning algorithms provided no meaningful improvement for discrimination compared with logistic regression, which suggests a lack of influential latent interactions among the analytes assessed in this study.Trial registration number Diabetes Prevention Program: NCT00004992; Diabetes Prevention Program Outcomes Study: NCT00038727.…”
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Enhancing IoT Security in 5G Networks by Reem Alzhrani, Mohammed Alliheedi

“…We compared the results of these algorithms with three machine learning methods: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Stochastic Gradient Descent (SGD). …”
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