Health poverty reduction effect of medical insurance in China’s middle-aged and elderly populations: a cross-sectional study by Haijun Yang, Rui Chen, Ye Li, Qunhong Wu, Linghan Shan, Bing Wu, Fang Yin, Yiyun Zhang, Yongqiang Lai, Xinwei Liu, Wanxin Tian, Xiyu Zhang, Yujuan Xu, Wenqing Miao, Baoguo Shi, Feifei Leng

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AI-Based Noise-Reduction Filter for Whole-Body Planar Bone Scintigraphy Reliably Improves Low-Count Images by Csaba Csikos, Sándor Barna, Ákos Kovács, Péter Czina, Ádám Budai, Melinda Szoliková, Iván Gábor Nagy, Borbála Husztik, Gábor Kiszler, Ildikó Garai

“…This study aimed to assess the performance of an AI-based bone scan noise-reduction filter on noisy, low-count images in a routine clinical environment. …”
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Effect of a health education program on reduction of pediculosis in school girls at Amphoe Muang, Khon Kaen Province, Thailand. by Manachai Yingklang, Chatchawan Sengthong, Ornuma Haonon, Rungtiwa Dangtakot, Porntip Pinlaor, Chulaporn Sota, Somchai Pinlaor

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Artificial Intelligence overview for optimizing production scheduling in a picture framing company by Krupnik-Worek Jadwiga, Skoczypiec Sebastian, Habel Jacek

“…In warehouse planning, AI optimizes inventory placement, automates processes, and enables predictive maintenance. In production, it improves scheduling, predicts machine failures, and personalizes products. …”
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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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Machine learning approach for optimizing usability of healthcare websites by Amandeep Kaur, Jaswinder Singh, Satinder Kaur

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Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

“…It was found that when using AB algorithms, greater accuracy is achieved, but the stability of the LSVM algorithm is higher. …”
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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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Introducing an Evolutionary Method to Create the Bounds of Artificial Neural Networks by Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis

“…From the conducted experiments, it appears that the proposed method reduced the average classification error by 30%, compared to the genetic algorithm, and the average regression error by 45%, as compared to the genetic algorithm.…”
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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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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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