Predicting stroke with machine learning techniques in a sub-Saharan African population by Benjamin Segun Aribisala, Deirdre Edward, Godwin Ogbole, Onoja M. Akpa, Segun Ayilara, Fred Sarfo, Olusola Olabanjo, Adekunle Fakunle, Babafemi Oluropo Macaulay, Joseph Yaria, Joshua Akinyemi, Albert Akpalu, Kolawole Wahab, Reginald Obiako, Morenikeji Komolafe, Lukman Owolabi, Godwin Osaigbovo, Akinkunmi Paul Okekunle, Arti Singh, Philip Ibinaye, Osahon Osawata, Adeniyi Sunday, Ijezie Chukwuonye, Carolyn Jenkins, Hemant K. Tiwari, Okechukwu Ogah, Ruth Y. Laryea, Daniel T. Lackland, Oyedunni Arulogun, Omotolani Ajala, Rufus Akinyemi, Bruce Ovbiagele, Steffen Sammet, Mayowa Owolabi

“…Accurate models are needed in Africa to predict and prevent stroke occurrence. The aim of this study was to identify the best machine learning (ML) algorithm for stroke prediction. …”
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Digital twin for real-time pressure vessels fatigue life prediction by Izat Khaled, Mohamed Bennebach, Dmytro Vasiukov, Modesar Shakoor, Salim Chaki

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A novel formula for predicting the ultimate compressive strength of the cylindrically curved plates by Do Kyun Kim, Andy Ming King Wong, Jinha Hwang, Shen Li, Nak-Kyun Cho

“…''The present study aims to develop an empirical formula to predict the ultimate compressive strength of unstiffened cylindrically curved plates. …”
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Developing serum proteomics based prediction models of disease progression in ADPKD by Hande Ö. Aydogan Balaban, Sita Arjune, Franziska Grundmann, Jan-Wilm Lackmann, Thomas Rauen, Philipp Antczak, Roman-Ulrich Müller

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Automated diabetes detection prediction system based on patients’ medical data by S.V. Pidopryhora, Yu.V. Bogoyavlenska

“…The development of an automated system for predicting diabetes detection is an extremely relevant task, especially given the rapid increase in the number of diabetes cases in Ukraine and worldwide. …”
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Non-Pharmacological Interventions for Chronic Pain Management: A Narrative Review by Mohammed Albesher, Mohammed AlKhalifah, Abdulaziz Hazazi, Ghassan Hakeem, Bader Almogbel

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Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The deep beam in load transfer is very important as well as difficult to design due to its shear stress problems. Accurate estimation of shear stress would help engineers to get a safer design. …”
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An illustration of multi-class roc analysis for predicting internet addiction among university students. by Nishat Tasnim Thity, Atikur Rahman, Adisha Dulmini, Mst Nilufar Yasmin, Rumana Rois

“…University students' backgrounds, depression, anxiety, stress, participation in physical activity, misbehaving with family members, memory loss symptoms, and being COVID-19-positive were selected as significant features for predicting IA. …”
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Prediction of Crushing Response for Metal Hexagonal Honeycomb under Quasi-Static Loading by Xinyu Geng, Yufei Liu, Wei Zheng, Yongbin Wang, Meng Li

“…The mathematical models of mean crushing stress and peak crushing stress for metal hexagonal honeycombs were predicted on the basis of simplified super element theory. …”
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Neuro-Fuzzy Model Evaluation for Enhanced Prediction of Mechanical Properties in AM Specimens by Emmanouil-Marinos Mantalas, Vasileios D. Sagias, Paraskevi Zacharia, Constantinos I. Stergiou

“…Experimental data collected from AM processes are used to train the ANFIS model, allowing it to predict outputs such as stress, strain, and Young’s modulus under various printing parameters values. …”
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Research on Accelerated Degradation Test Design and Life Prediction for Aluminum Electrolytic Capacitor by YANG Tao, WANG Xu, XIAO Jianglin

“…Starting from the structure and degradation mechanism of aluminum electrolytic capacitor, this paper designs an accelerated degradation test with temperature as the accelerated sensitive stress, uses the accelerated degradation data for life prediction, and gives a top-down design direction for extending the life of aluminum electrolytic capacitors. …”
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Do Depressive Traits and Hostility Predict Age-Related Decline in General Intelligence? by Erik Lykke Mortensen, John Calvin Barefoot, Kirsten Avlund

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Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome by Miranda C. Mudge, Michael Riffle, Gabriella Chebli, Deanna L. Plubell, Tatiana A. Rynearson, William S. Noble, Emma Timmins-Schiffman, Julia Kubanek, Brook L. Nunn

“…Abstract Harmful algal blooms (HABs) have become a worldwide environmental and human health problem, stressing the urgent need for a reliable forecasting tool. …”
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MODIFIABLE AND NON-MODIFIABLE RISK FACTORS IN PREDICTING THE RECURRENCE OF ATRIAL FIBRILLATION IN PATIENTS WITH ARTERIAL HYPERTENSION by M. S. Arakelyan, N. G. Poteshkina, P. A. Mogutova

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Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

“…In order to accurately predict the rockburst intensity level of the railway tunnel, the rock stress coefficient σθ/σc, rock brittleness coefficient σc/σt, and elastic energy index Wet are used as evaluation indexes of rockburst intensity, and a BP neural network rockburst prediction model based on hybrid particle swarm optimization algorithm is proposed. …”
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Study on the Prediction of the Height of Two Zones in the Overlying Strata under a Strong Shock by Xingping Lai, Bowei Liu, Pengfei Shan, Feng Cui, Yun Zhang, Xudong Zhang, Rui Bai, Xuan Wu

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Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation by Pascal B. Meyre, Stefanie Aeschbacher, Steffen Blum, Tobias Reichlin, Moa Haller, Nicolas Rodondi, Andreas S. Müller, Alain Bernheim, Jürg Hans Beer, Giorgio Moschovitis, André Ziegler, Bianca Wahrenberger, Elia Rigamonti, Giulio Conte, Philipp Krisai, Leo H. Bonati, Stefan Osswald, Michael Kühne, David Conen

“…We identify 5 biomarkers including D-dimer, growth differentiation factor 15 (GDF-15), interleukin-6 (IL-6), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and high-sensitivity troponin T (hsTropT) that independently predict cardiovascular death, stroke, myocardial infarction, and systemic embolism, significantly enhancing predictive accuracy. …”
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Optimizing corn yield prediction: Integrating multi-temporal UAS data and machine learning by Huihui Zhang, Yuting Zhou, Shengfang Ma, Kevin Yemoto

“…The integration of VNIR and LWIR imagery improves yield prediction accuracy, particularly in water-stressed conditions, highlighting the importance of advanced sensing technologies and complex models such as RF and GB. …”
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Multi‐trait multi‐environment genomic prediction of preliminary yield trial in pulse crop by Rica Amor Saludares, Sikiru Adeniyi Atanda, Lisa Piche, Hannah Worral, Francoise Dariva, Kevin McPhee, Nonoy Bandillo

“…Multi‐trait multi‐environment enabled genomic prediction (MTME‐GP) offers a valuable alternative to predict missing phenotypes of selection candidates for multiple traits and diverse environments. …”
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Unveiling postpartum PTSD: predicting risk factors using decision trees and logistic regression in Chinese women by Xiao Fei Nie, Lan Lan Xu, Wen Ping Guo, Jin Hui Li, Li Cheng, Tao Tao Zhang, Jun-Yan Li

“…However, no studies have yet integrated both approaches to investigate postpartum posttraumatic stress disorder (PP-PTSD). This study aims to explore the factors associated with postpartum posttraumatic stress disorder (PP-PTSD) in Chinese women using decision tree and logistic regression models, while also comparing the predictive performance of both approaches. …”
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