Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems by Mohamed Medani, Ghada Moh. Samir Elhessewi, Mohammed Alqahtani, Somia A. Asklany, Sulaiman Alamro, Da’ad Albalawneh, Menwa Alshammeri, Mohammed Assiri

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A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases by Norma Latif Fitriyani, Muhammad Syafrudin, Nur Chamidah, Marisa Rifada, Hendri Susilo, Dursun Aydin, Syifa Latif Qolbiyani, Seung Won Lee

“…This research presents a novel prediction model for CVDs utilizing a bagging algorithm that incorporates histogram gradient boosting as the estimator. …”
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A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
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Enhancing Injector Performance Through CFD Optimization: Focus on Cavitation Reduction by Jose Villagomez-Moreno, Aurelio Dominguez-Gonzalez, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes, Angel Perez-Cruz

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The Influence of Network Structural Preference on Link Prediction by Yongcheng Wang, Yu Wang, Xinye Lin, Wei Wang

“…However, in the social network, link prediction may raise concerns about privacy and security, because, through link prediction algorithms, criminals can predict the friends of an account user and may even further discover private information such as the address and bank accounts. …”
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Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

“…The study objective is to build a model based on machine learning that can predict the detection of SARS-CoV-2 from medical data. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…Future research should focus on integrating multiple datasets and exploring more complex ML algorithms to enhance prediction accuracy and generalization. …”
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Machine Learning and the Conundrum of Stroke Risk Prediction by Yaacoub Chahine, Matthew J Magoon, Bahetihazi Maidu, Juan C del Álamo, Patrick M Boyle, Nazem Akoum

“…The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. Standard algorithms predict risk using regression-based statistical associations, which, while useful and easy to use, have moderate predictive accuracy. …”
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Location Prediction on Trajectory Data: A Review by Ruizhi Wu, Guangchun Luo, Junming Shao, Ling Tian, Chengzong Peng

“…This survey provides a comprehensive overview of location prediction, including basic definitions and concepts, algorithms, and applications. …”
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Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems by Benabdallah Naima, Belabbas Belkacem, Tahri Ahmed, Habib Benbouhenni, Bouddou Riyadh, Heroual Samira, Zaidi Sarra, Z. M. S. Elbarbary, Salman Arafath Mohammed

Subjects: “…Modified finite control set model predictive control…”
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A Unmanned Aerial Vehicle-Based Image Information Acquisition Technique for the Middle and Lower Sections of Rice Plants and a Predictive Algorithm Model for Pest and Disease Detection by Xiaoyan Guo, Yuanzhen Ou, Konghong Deng, Xiaolong Fan, Ruitao Gao, Zhiyan Zhou

“…Aiming at the technical bottleneck of monitoring rice stalk, pest, and grass damage in the middle and lower parts of rice, this paper proposes a UAV-based image information acquisition method and disease prediction algorithm model, which provides an efficient and low-cost solution for the accurate early monitoring of rice diseases, and helps improve the scientific and intelligent level of agricultural disease prevention and control. …”
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Modeling of Energy Management System for Fully Autonomous Vessels with Hybrid Renewable Energy Systems Using Nonlinear Model Predictive Control via Grey Wolf Optimization Algorithm by Harriet Laryea, Andrea Schiffauerova

“…The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. …”
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Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study by Ji-Hyun Kim, Chi-Heum Cho, In-Cheol Kim, Kwang Joon Kim, KyungHyun Lee, Eun Yeong Ha, Sun Hyo Park, Gyeong Im Yu, Byung Eun Ahn, Yeeun Jeong, Joo-Yun Won, Taeyong Sim, Hochan Cho, Ki-Byung Lee

“…VitalCare-SEPsis Score (VC-SEPS) is a deep learning-based algorithm that predicts sepsis and monitors patient conditions based on electronic medical record data. …”
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Big data, dementia prediction and knowledge organization by D. Grant Campbell

“…This paper uses principles of knowledge organization to explore the application of big data algorithms to the task of predicting dementia diagnoses. …”
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Voltage-based prediction technique for efficient MPPT method for SPV systems under non-uniform insolation and partial shading conditions by Haider A. Mohamed-Kazim, Ahmed Hussein Shatti, Ahmed Aldhahab, Ikhlas Abdel-Qader, Sarmad K. Ibrahim, Rusul Noori Saraj

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Malware prediction technique based on program gene by Da XIAO, Bohan LIU, Baojiang CUI, Xiaochen WANG, Suoxing ZHANG

“…With the development of Internet technology,malicious programs have risen explosively.In the face of executable files without source,the current mainstream malware detection uses feature detection based on similarity,with lack of analysis of malicious sources.To resolve this status,the definition of program gene was raised,a generic method of extracting program gene was designed,and a malicious program prediction method was proposed based on program gene.Utilizing machine learning and deep-learning algorithms,the forecasting system has good prediction ability,with the accuracy rate of 99.3% in the deep-learning model,which validates the role of program gene theory in the field of malicious program analysis.…”
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Early Detection of Congenital Heart Diseases among Infants Using Artificial Neural Network Algorithm by Lucy Ifeyinwa Ezigbo, Anthony Kwubeghari, Francis Okoye

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Annotation-free prediction of microbial dioxygen utilization by Avi I. Flamholz, Joshua E. Goldford, Philippa A. Richter, Elin M. Larsson, Adrian Jinich, Woodward W. Fischer, Dianne K. Newman

“…As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. …”
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Real-Time Football Match Prediction Platform by An Zhongqi

“…Future work will focus on enhancing model algorithms and incorporating more complex data sources, such as social media sentiment analysis, to further improve prediction accuracy.…”
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CNN-based Gender Prediction in Uncontrolled Environments by Kazım Yıldız, Engin Güneş, Anil Bas

“…In this study, Convolutional Neural Networks (CNN), one of the deep learning algorithms, was used. The model created with this algorithm was trained with facial images and gender prediction was made. …”
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