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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Resolution of the consensus of the Russian Federation experts on the diagnosis and treatment of osteoarthritis, 2022 by A. M. Lila, V. I. Mazurov, A. I. Martynov, N. V. Zagorodny, L. I. Alekseeva, N. V. Chichasova, A. E. Karateev, A. V. Naumov, E. V. Zonova, A. P. Rachin, E. A. Taskina

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Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007–2018 by Efrain Riveros Perez, Bibiana Avella-Molano

“…The performance of five machine learning algorithms (logistic regression, support vector machine, random forest, XGBoost and CatBoost) was evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC). …”
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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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Postdigital Bodies: Young People’s Experiences of Algorithmic, Tech-Facilitated Body Shaming and Image-Based Sexual Abuse during and after the COVID-19 Pandemic in England by Jessica Ringrose, Betsy Milne, Tanya Horeck, Kaitlynn Mendes

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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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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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Power Load Prediction Based on Fractal Theory by Liang Jian-Kai, Carlo Cattani, Song Wan-Qing

“…The attractor is obtained using an improved deterministic algorithm based on the fractal interpolation function, a day’s load is predicted by three days’ historical loads, the maximum relative error is within 3.7%, and the average relative error is within 1.6%. …”
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Machine Learning Approaches for Software Defect Prediction by Hijab Zehra Zaidi, Ubaid Ullah, Muddassira Arshad, Hanan Aljuaid, Muhammad Arslan Rauf, Nadeem Sarwar, Rimsha Sajid

“…The paper reviews the use of machine learning algorithms in software defect prediction framework’s bug prediction while assessing their performance across multiple environments. …”
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Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…Many analyses include multiple Machine Learning algorithms for various disease assessments and predictions to improve overall issues. …”
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Photovoltaic Generation Prediction of CCIPCA Combined with LSTM by E. Zhu, D. Pi

“…The model is compared with Markov chain power generation prediction model and GA-BP power generation prediction model. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou, Umesh Kumar Lilhore, Poongodi M, Tao Hai, Sarita Simaiya, Dayang Norhayati Abang Jawawi, Deema Mohammed Alsekait, Sachin Ahuja, Cresantus Biamba, Mounir Hamdi

“…Therefore it requires more time to predict the best possible solution. Few techniques can perhaps generate an ideal solution under a polynomial period to fix these issues. …”
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Robust parameter inversion of coal mining subsidence based on the combination of RANSAC and DE algorithms by Yuanfei Chen, Lei Wang

“…Currently, methods for obtaining subsidence prediction parameters based on surface measurement data primarily rely on inversion algorithms. …”
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Study of line spectra emitted by hydrogen isotopes in tokamaks through Deep-Learning algorithms by N. Saura, M. Koubiti, S. Benkadda

“…The prediction accuracy in these cases is comparable to the training accuracy.…”
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Development of immune-derived molecular markers for preeclampsia based on multiple machine learning algorithms by Zhichao Wang, Long Cheng, Guanghui Li, Huiyan Cheng

“…Further validation in larger cohorts could lead to their clinical application in PE prediction and treatment.…”
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A Genetic-Algorithms Matrix-Factorization-Based Recommender System Model Using Tags by Manal Almaayah, Yousef Kilani, Ayoub Alsarhan, Mohammad Aljaidi, Mohammed Alshammari, Aadil Alshammari

“…It then uses Genetic Algorithms to predict the unknown rated items. It aims at improving accuracy, speeding up the recommendation process, increasing transparency and interaction. …”
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