Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya by Yashon O. Ouma, Clinton O. Okuku, Evalyne N. Njau

“…The process of predicting water quality over a catchment area is complex due to the inherently nonlinear interactions between the water quality parameters and their temporal and spatial variability. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…The improved Elman neural network model has the advantage of high prediction accuracy and can be applied to the prediction of the corrosion rate of 3C steel in the marine environment.…”
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Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology by Matteo P. Ferla, Rubén Sánchez-García, Rachael E. Skyner, Stefan Gahbauer, Jenny C. Taylor, Frank von Delft, Brian D. Marsden, Charlotte M. Deane

“…Scientific contribution This work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. …”
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Data-Driven Approach for the Prediction of In Situ Gas Content of Deep Coalbed Methane Reservoirs Using Machine Learning: Insights from Well Logging Data by Qian Zhang, Shuheng Tang, Songhang Zhang, Zhaodong Xi, Tengfei Jia, Xiongxiong Yang, Donglin Lin, Wenfu Yang

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Prediction Efficiency of Postoperative Acute Kidney Injury in Acute Stanford Type A Aortic Dissection Patients with Renal Resistive Index and Semiquantitative Color Doppler by Huai Qin, Yaqiong Li, Nan Zhang, Tiezhu Wang, Zhanming Fan

“…Both postoperative RRI and SQC Doppler grade can be obtained rapidly by bedside ultrasound, which is a good tool for early prediction for postoperative PAKI.…”
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Diagnostic prediction model for screening of elevated low-density and non-high-density lipoproteins in young Thai adults between 20 and 40 years of age by Phichayut Phinyo, Wuttipat Kiratipaisarl, Vithawat Surawattanasakul, Wachiranun Sirikul

“…However, 94.4% of Thai young adult are unaware of their condition. A diagnostic prediction model may assist in screening and alleviating underdiagnosis.Objectives Development and internal validation of diagnostic prediction models on elevated LDL-C (≥160 mg/dL) and non-HDL-C (≥160 mg/dL).Methods Retrospective, single-centre, tertiary-care hospital annual health examination data from 29 March 2018 to 30 August 2023 was analysed. …”
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Optimizing the Prediction Accuracy of Friction Capacity of Driven Piles in Cohesive Soil Using a Novel Self-Tuning Least Squares Support Vector Machine by Doddy Prayogo, Yudas Tadeus Teddy Susanto

“…This research presents a novel hybrid prediction technique, namely, self-tuning least squares support vector machine (ST-LSSVM), to accurately model the friction capacity of driven piles in cohesive soil. …”
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Prediction of the cutting tool wear during dry hard turning of AISI D2 steel by using models based on Learning process and GA polyfit by Khaled Djellouli, Kamel Haddouche, Mostefa Belarbi, Zoubir Aich

“… In this paper, we are interested in the prediction of flank wear through dry hard turning of AISI D2 steel with a mixed alumina insert. …”
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Harvesting Solar Energy: Prediction of Daily Global Horizontal Irradiance Using Artificial Neural Networks and Assessment of Electrical Energy of Photovoltaic at North Eastern Ethiopia by Tegenu A. Woldegiyorgis, Abera D. Assamnew, Gezahegn A. Desalegn, Sentayehu Y. Mossie

“…Because of its variability and nonlinear characteristics, it needs accurate prediction techniques in a specific location. Thus, the objectives of this article were: (i) assessing daily global horizontal irradiance using network types‐activation functions of artificial neural network (ANN); and (ii) evaluating the daily energy delivered to and available on photovoltaic (PV) cells of GaAs at Kemissie, Woldiya, and Hayk, in the northeastern part of Ethiopia. …”
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Elevated Circulating Adipocyte-Fatty Acid Binding Protein Levels Predict Incident Ischemic Cardiovascular Events in a Longitudinal and Prospective AMI Aging Study by Zhao X, Zhao H, Chen R, Zhou J, Li N, Li J, Yan S, Liu C, Zhou P, Chen Y, Song L, Yan H

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Optimizing Parkinson’s Disease Prediction: A Comparative Analysis of Data Aggregation Methods Using Multiple Voice Recordings via an Automated Artificial Intelligence Pipeline by Zhengxiao Yang, Hao Zhou, Sudesh Srivastav, Jeffrey G. Shaffer, Kuukua E. Abraham, Samuel M. Naandam, Samuel Kakraba

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Predictive Ability of Visit-to-Visit Variability of HbA1c Measurements for the Development of Diabetic Kidney Disease: A Retrospective Longitudinal Observational Study by Yunyi Yan, Nozomi Kondo, Kentaro Oniki, Hiroshi Watanabe, Tadashi Imafuku, Yuki Sakamoto, Takuro Shigaki, Akari Maruyama, Hitomi Nakazawa, Tetsuya Kaneko, Ayami Morita, Akira Yoshida, Hitoshi Maeda, Toru Maruyama, Hideaki Jinnouchi, Junji Saruwatari

“…HbA1c-AUC, a novel index of HbA1c variability, may be a potent prognostic indicator in predicting the risk of microalbuminuria.…”
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COVID-19 Deep Learning Prediction Model Using Publicly Available Radiologist-Adjudicated Chest X-Ray Images as Training Data: Preliminary Findings by Mohd Zulfaezal Che Azemin, Radhiana Hassan, Mohd Izzuddin Mohd Tamrin, Mohd Adli Md Ali

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The Predictive Value of Urinary Kidney Injury Molecular 1 for the Diagnosis of Contrast-Induced Acute Kidney Injury after Cardiac Catheterization: A Meta-Analysis by Qing Li, Yimin Huang, Weifeng Shang, Ying Zhang, Yanyan Liu, Gang Xu

“…However, the predictive value of uKIM-1 for diagnosis of contrast-induced acute kidney injury (CI-AKI) remains unclear. …”
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Predictive and spatial analysis for estimating the impact of sociodemographic factors on contraceptive use among women living with HIV/AIDS (WLWHA) in Kenya: Implications for policies and practice by Menkeoma Laura Okoli, Samuel Alao, Somtochukwu Ojukwu, Nnadozie C Emechebe, Asuelimen Ikhuoria, Kevin E Kip

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The role of Anti-PAD4, Anti-CarP, and Anti-RA33 antibodies combined with RF and ACPA in predicting abatacept response in rheumatoid arthritis by Alberto Floris, Maria Maddalena Angioni, Mattia Fadda, Micaela Rita Naitza, Mattia Congia, Elisabetta Chessa, Matteo Piga, Alberto Cauli

“…Conclusion This study highlights the potential benefits of using a combined assessment of ACPA aPAD4 and aCarP in predicting effectiveness of ABT in RA.…”
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Evaluation of Wisconsin and CaPTHUS Indices Usefulness for Predicting Monoglandular and Multiglandular Disease in Patients with Primary Hyperparathyroidism through the Analysis of a Single-Center Experience by Loredana De Pasquale, Eleonora Lori, Antonio Mario Bulfamante, Giovanni Felisati, Luca Castellani, Alberto Maria Saibene

“…Based on our experience, CaPTHUS test and Wisconsin index were not so useful in predicting multiglandular disease as ioPTH.…”
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Comparison between the HLA-B∗58 : 01 Allele and Single-Nucleotide Polymorphisms in Chromosome 6 for Prediction of Allopurinol-Induced Severe Cutaneous Adverse Reactions by Niwat Saksit, Nontaya Nakkam, Parinya Konyoung, Usanee Khunarkornsiri, Wongwiwat Tassaneeyakul, Pansu Chumworathayi, Sirimas Kanjanawart, Chonlaphat Sukasem, Alisara Sangviroon, Oranuch Pattanacheewapull, Wichittra Tassaneeyakul

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Identification of a Seven-lncRNA-mRNA Signature for Recurrence and Prognostic Prediction in Relapsed Acute Lymphoblastic Leukemia Based on WGCNA and LASSO Analyses by Haiyan Qi, Long Chi, Xiaogang Wang, Xing Jin, Wensong Wang, Jianping Lan

“…This study developed an lncRNA-mRNA integrated classifier for the prediction of recurrence and prognosis in relapsed childhood ALL by using several transcriptome data. …”
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Comparative evaluation of APRI and MELD scores in the prediction of complications of chronic hepatitis in patients infected with hepatitis B or C viruses in Lubumbashi, democratic republic of Congo by Arsène Kabamba-Tshikongo, Adolphe Baleebenga, Bernard Kalunga-Tompa, Claude Mwamba-Mulumba, Henry Manya-Mboni, Cedrick Mutombo-Shakalenga, Pierrot Mwamba-Tshilumba, Sébastien Bontems, Géraldine Dessilly, Benoît Kabamba-Mukadi, Albert Longanga-Otshudi

“…The objective of this study was to compare APRI and MELD scores in the prediction of fibrosis in patients with chronic viral hepatitis B in Lubumbashi. …”
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