Factors Predicting Self-Care Behaviors among Low Health Literacy Hypertensive Patients Based on Health Belief Model in Bushehr District, South of Iran by Azam Larki, Rahim Tahmasebi, Mahnoush Reisi

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A prediction risk score for HIV among adolescent girls and young women in South Africa: identifying those in need of HIV pre-exposure prophylaxis by Reuben Christopher Moyo, Darshini Govindasamy, Samuel Om Manda, Peter Suwirakwenda Nyasulu

“…The model’s positive predictive value was 68.2% and a negative predictive value of 85.8%. …”
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An optimized deep-forest algorithm using a modified differential evolution optimization algorithm: A case of host-pathogen protein-protein interaction prediction by Jerry Emmanuel, Itunuoluwa Isewon, Jelili Oyelade

“…Additionally, the optimized model predicted seven novel host-pathogen interactions. Finally, the model was implemented as a web application which is accessible at http://dfh3pi.covenantuniversity.edu.ng.…”
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Prediction of Favorable Carbonate Reservoirs under Extremely Thick Salts via Poststack Facies-Controlled and Prestack Zoeppritz Equation Inversions in the Santos Basin of Brazil by Sheng Zhang, Suoliang Chang, Handong Huang, Yinping Dong, Youyi Shen, Yaneng Luo, Baoheng Zhu

“…The application of this method in carbonate reservoirs under extremely thick salts in the Santos Basin of Brazil indicates the feasibility and practicality of the proposed integrated prediction method.…”
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Regarding “Enhancing Predictive Accuracy for Acute Herpetic Neuralgia Treatment: A Fresh Perspective on Pulsed Radiofrequency Therapy Research” [Response to Letter] by Zhao C, Lu Z, Hua B, Yue J, Yang Q, Ni H, Yao M

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Mortality Risk Prediction in Patients With Antimelanoma Differentiation–Associated, Gene 5 Antibody–Positive, Dermatomyositis–Associated Interstitial Lung Disease: Algorithm Development and Validation by Hui Li, Ruyi Zou, Hongxia Xin, Ping He, Bin Xi, Yaqiong Tian, Qi Zhao, Xin Yan, Xiaohua Qiu, Yujuan Gao, Yin Liu, Min Cao, Bi Chen, Qian Han, Juan Chen, Guochun Wang, Hourong Cai

“…There is an urgent need for a reliable prediction model, accessible via an easy-to-use web-based tool, to evaluate the risk of death. …”
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A Comparison of the Glasgow Coma Scale Score with Full Outline of Unresponsiveness Scale to Predict Patients’ Traumatic Brain Injury Outcomes in Intensive Care Units by Rostam Jalali, Mansour Rezaei

“…The FOUR scale has a better prediction for death than GCS. Conclusion. It appears that FOUR scale had better predictive power for mortality and may be a suitable alternative or complementary tool for GCS.…”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…This study aims to leverage the database to build a predictive model for early identification of high-risk patients. …”
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Physiological and behavioural resistance of malaria vectors in rural West-Africa: a data mining study to address their fine-scale spatiotemporal heterogeneity, drivers, and predictability by Taconet, Paul, Soma, Dieudonné Diloma, Zogo, Barnabas, Mouline, Karine, Simard, Frédéric, Koffi, Alphonsine Amanan, Dabiré, Roch Kounbobr, Pennetier, Cédric, Moiroux, Nicolas

“…The objectives were i) to assess the small-scale spatial and temporal heterogeneity of physiological resistance to insecticide and behavioural resistance phenotypes, ii) to better understand their drivers, and iii) to assess their spatio-temporal predictability, at scales that are consistent with operational action. …”
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Combination of White Blood Cell Count to Mean Platelet Volume Ratio and Neutrophil-to-Platelet Ratio Predicts Long-Term Adverse Events in Patients with MINOCA by Ayman A. Mohammed, Lu Liu, Redhwan M. Mareai, Abdul-Quddus Mohammed, Guoqing Yin, Shekhar Singh, Yawei Xu, Fuad A. Abdu, Wenliang Che

“…High WMR and NPR separately or in combination were correlated with increased risk of MACE among MINOCA patients, suggesting WMR and NPR may assist as a reliable inflammatory marker in risk prediction of MINOCA patients.…”
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Triglyceride-glucose index predicts adverse cardiovascular events in patients with H-type hypertension combined with coronary heart disease: a retrospective cohort study by Changjiang Li, Shun Zhao, Yingkai Li, Songyuan He, Wen Jian, Yanci Liu, Zichao Cheng, Hongyu Peng

“…Conclusion The TyG index may be an independent risk factor for predicting adverse postoperative cardiovascular events in patients with H-type hypertension combined with CHD, indicating its potential significance in improving risk stratification strategies. …”
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Artificial neural network systems to predict the response to sintilimab in squamous-cell non-small-cell lung cancer based on data of ORIENT-3 study by Tongji Xie, Guangyu Fan, Le Tang, Puyuan Xing, Yuankai Shi

“…Abstract Background Existing biomarkers and models for predicting response to programmed cell death protein 1 monoclonal antibody in advanced squamous-cell non-small cell lung cancer (sqNSCLC) did not have enough accuracy. …”
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Machine learning based predictive model and genetic mutation landscape for high-grade colorectal neuroendocrine carcinoma: a SEER database analysis with external validation by Ruixin Wu, Ruixin Wu, Sihao Chen, Sihao Chen, Yi He, Yi He, Ya Li, Song Mu, Aishun Jin, Aishun Jin

“…The most common mutations of CNEC identified in the COSMIC database were TP53, KRAS, and APC.ConclusionsIn this study, a refined machine learning predictive model was developed to assess the prognosis of HCNEC accurately and we briefly analyzed its genomic features, which might offer a valuable tool to address existing clinical challenges.…”
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Endpoint carbon content and temperature prediction model in BOF steelmaking based on posterior probability and intra-cluster feature weight online dynamic feature selection by Wang Haodong, Liu Hui, Chen FuGang, Li Heng, Xue XiaoJun

“…Finally, the dynamically selected features are used in a regression model to predict the carbon content and temperature of the BOF steelmaking process data. …”
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Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA by Jun-Yu Zhu, An-Qi Lyu, Zhang-Ting Wang, Wai-Yee Chan, Tao Qin, Kai-Kei Miu, He-Rui Yao

“…A 40 immune-related lncRNA pair (IRLP) signature including 43 irlncRNAs was built, with high sensitivity and specificity for the prediction of survival in different molecular subtypes of BRCA. …”
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Influenza Infection Screening Tools Fail to Accurately Predict Influenza Status for Hospitalized Patients During Pandemic H1N1 Influenza Season by Sunita Mulpuru, Virginia R Roth, Nadine Lawrence, Alan J Forster

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Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model. by Jonathan Halama, Robert McKane, Bradley Barnhart, Paul Pettus, Allen Brookes, Kevin Djang, Vivian Phan, Sonali Chokshi, James Graham

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Triglyceride-glucose index in predicting the risk of new-onset diabetes in the general population aged 45 years and older: a national prospective cohort study by Yingqi Shan, Qingyang Liu, Tianshu Gao

“…Conclusions TyG index can be used as a risk factor for predicting new-onset diabetes in the middle-aged and elderly population in China. …”
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Prediction and Analysis of metabolic mechanism for regional water system from the perspective of quantity-quality collaborative control——A case study of Zhejiang Province, China by Siqi Li, Yang Zhang, Tianqi Liu, Jinbo Zhang, Huaicheng Guo, Xiao Pu, Lu Lu, Changbo Qin

“…Thus, the objective of this study is to predict and analyze the metabolic mechanism for regional water system from the perspective of quantity-quality collaborative control. …”
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Toward accurate prediction of carbon dioxide (CO2) compressibility factor using tree-based intelligent schemes (XGBoost and LightGBM) and equations of state by Behnam Amiri-Ramsheh, Aydin Larestani, Saeid Atashrouz, Elnaz Nasirzadeh, Meriem Essakhraoui, Ali Abedi, Mehdi Ostadhassan, Ahmad Mohaddespour, Abdolhossein Hemmati-Sarapardeh

“…To this end, a comprehensive databank from the literature is employed, which contains 2118 data points over extensive ranges of pressures and temperatures. The proposed models predict the CO2 Z-factor with respect to reduced temperature (Tr) and reduced pressure (Pr). …”
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