Development and Evaluation of a Hypertension Prediction Model for Community-Based Screening of Sleep-Disordered Breathing by Feng T, Shan G, Hu Y, He H, Pei G, Zhou R, Ou Q

“…This study aimed to develop a hypertension prediction model tailored for primary care physicians, utilizing simple, readily available predictors derived from type IV sleep monitoring devices.Patients and Methods: Participants were recruited from communities in Guangdong Province, China, between April and May 2021. …”
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Evaluation and Comparison of the PREVENT and Pooled Cohort Equations for 10‐Year Atherosclerotic Cardiovascular Risk Prediction by Hui Zhou, Yiyi Zhang, Matt M. Zhou, Soon Kyu Choi, Kristi Reynolds, Teresa N. Harrison, Brandon K. Bellows, Andrew E. Moran, Lisandro D. Colantonio, Norrina B. Allen, Monika M. Safford, Jaejin An

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Evaluating the Validity of Risk Scoring in Predicting Pacemaker Rates following Transcatheter Aortic Valve Replacement by Alexander M. Spring, Michael A. Catalano, Vikram Prasad, Bruce Rutkin, Elana Koss, Alan Hartman, Pey-Jen Yu

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Construction and evaluation of nomogram for risk prediction of cognitive impairment in chronic obstructive pulmonary disease comorbidity by JiaFeng Luo, Wen Yang, Yang Liu, HongLian Ji, XinRan Li, Jing Bai, TieJun Liu, WeiBin Chen, Li Xiao, GuoXin Mo, JingShan Bai, CongHui Liu, WenQiang Li, AiShuang Fu, YanLei Ge

“…The aim of this study was to construct a nomogram prediction model for the risk of comorbid cognitive impairment in COPD patients and to evaluate its clinical application. …”
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A systematic literature review of swimming performance prediction: methods, datasets, techniques and research trends by Ari Tri Fitrianto, Oddie Barnanda Rizky, Edi Rahmadi, Asary Ramadhan

“…Objective: This paper provides an extensive and systematic review of research in swimming performance prediction published from 2014 to 2024. Method: This swimming performance prediction research was conducted with a Systematic Literature Review (SLR). …”
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Comparative Analysis of Nonlinear Methods for Multivariable Water Level Prediction: The Case Study of the Atrato River by Jackson B. Renteria-Mena, Douglas Plaza, Eduardo Giraldo

“…In addition, a short-term water level prediction is developed for incorporation into a flood early warning system. …”
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Prediction of Auditory Performance in Cochlear Implants Using Machine Learning Methods: A Systematic Review by Beyza Demirtaş Yılmaz

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Risk Factors of Severe Disease and Methods for Clinical Outcome Prediction in Patients with COVID-19 (Review) by S. V. Sokologorskiy, A. M. Ovechkin, I. V. Khapov, M. E. Politov, E. L. Bulanova

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Data Augmentation and Deep Learning Methods for Pressure Prediction in Ignition Process of Solid Rocket Motors by Huixin Yang, Pengcheng Yu, Yan Cui, Bixuan Lou, Xiang Li

“…By comparison, the AGN-CBiLSTM method has a higher prediction accuracy with a percentage error of 3.27% between the predicted and actual data. …”
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The Comparison of Classical Statistical and Machine Learning Methods in Prediction of Thrombosis in Patients with Acute Myeloid Leukemia by Ilija Doknić, Mirjana Mitrović, Zoran Bukumirić, Marijana Virijević, Nikola Pantić, Nikica Sabljić, Darko Antić, Živko Bojović

“…This thesis explores the potential of data science (DS) methods for predicting venous thrombosis in patients with acute myeloid leukemia. …”
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Using Deep Learning (CNN, RNN, LSTM, GRU) methods for the prediction of Protein Secondary Structure by Ezgi Çakmak, İhsan Hakan Selvi

“…Many emerging methods, including machine learning, as well as deep learning, have been used to predict the secondary structure of proteins and comprise a crucial part of Structural Bioinformatics. …”
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Assessing the performance of 28 pathogenicity prediction methods on rare single nucleotide variants in coding regions by Jee Yeon Heo, Ju Han Kim

“…Ten evaluation metrics were employed to comprehensively assess the predictive performance of each method. …”
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IMPLEMENTATION OF BACKPROPAGATION AND HYBRID ARIMA-NN METHODS IN PREDICTING ACCURACY LEVELS OF RAINFALL IN MAKASSAR CITY by Hisyam Ihsan, Irwan Irwan, Andi Illa Erviani Nensi

“…Using a gradient descent algorithm, backpropagation adjusts synaptic weights based on the error between the network's prediction and actual training data values. In this study, a comparison was made between the Backpropagation method and Hybrid ARIMA-NN in forecasting rainfall in Makassar City. …”
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Machine Learning and Deep Learning for Loan Prediction in Banking: Exploring Ensemble Methods and Data Balancing by Eslam Hussein Sayed, Amerah Alabrah, Kamel Hussein Rahouma, Muhammad Zohaib, Rasha M. Badry

“…The prediction of loan defaults is crucial for banks and financial institutions due to its impact on earnings, and it also plays a significant role in shaping credit scores. …”
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General models for predicting the liquid thermal conductivity of fatty acid esters based on smart methods by Chou-Yi Hsu, Ahmad Mohsin, Ramdevsinh Jhala, Nagaraj Patil, Debasish Shit, V.K. Bupesh Raja, Manoj Kumar Ojha, Abinash Mahapatro, Deepak Gupta, Fereydoon Ranjbar

“…A general and straightforward thermal conductivity correlation was also constructed employing the Gene Expression Programming (GEP) method. Evaluations based on statistical indices and visual techniques demonstrated that all of the developed models are capable of predicting thermal conductivity with a high degree of accuracy, because the majority of their predictions fell within a ± 2 % error band. …”
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Predicting metabolic dysfunction associated steatotic liver disease using explainable machine learning methods by Yihao Yu, Yuqi Yang, Qian Li, Jing Yuan, Yan Zha

“…With 50 medical characteristics easily obtained, six ML algorithms were used to develop prediction models. Several evaluation parameters were used to compare the predictive performance, including the area under the receiver-operating-characteristic curve (AUC) and precision-recall (P-R) curve. …”
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LEVERAGING MACHINE LEARNING METHODS IN PREDICTING AND ANALYZING THE ASSOCIATION BETWEEN DIETARY INFLAMMATORY INDEX AND ALOPECIA by Mohammed Sarwat M Salih, Hawal Lateef Fateh, Soran Abdulkarim Pasha, Hassan M Tawfiq

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Impact of different genomic relationship matrix construction methods on the accuracy of genomic prediction in different species by Shiyi Wang, Yingjia Wei, Dengying Liu, Xiangzhe Zhang, Qishan Wang, Yuchun Pan, Peipei Ma

“…Although various methods for G-matrix construction have been proposed, the performance of these methods across different species has not been thoroughly compared.MethodsThis study systematically evaluated the performance of six genomic relationship matrix (G-matrix) construction methods in improving the prediction accuracy of GBLUP models across four species: pigs, bulls, wheat, and mice. …”
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Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods by Bin Zhang, Shengsheng Huang, Chenxing Zhou, Jichong Zhu, Tianyou Chen, Sitan Feng, Chengqian Huang, Zequn Wang, Shaofeng Wu, Chong Liu, Xinli Zhan

“…The research aims to develop an ML-based nomogram model analyzing clinical and demographic factors to estimate hospital length of stay (LOS). Accurate AHD predictions enable efficient resource allocation, improved patient care, and potential cost reduction in healthcare.Methods The study selected CS patients undergoing cervical spine surgery and investigated their medical data. …”
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Optimizing and Evaluation of Scour Depth Prediction Techniques for Columns as a Component of Complex Bridge Piers by Ata Amini, Thamer Mahmmod, Abdul Ghazali

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