CropCast: Harvesting the future with interfused machine learning and advanced stacking ensemble for precise crop prediction by Chetan Raju, Ashoka D.V., Ajay Prakash B.V.

Get full text

Agricultural GDP exposure to drought and its machine learning-based prediction in the Jialing River Basin, China by Xinzhi Wang, Qingxia Lin, Zhiyong Wu, Yuliang Zhang, Changwen Li, Ji Liu, Shinan Zhang, Songyu Li

Get full text

A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

Get full text

Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

Get full text

Application of machine learning algorithms and SHAP explanations to predict fertility preference among reproductive women in Somalia by Jamilu Sani, Salad Halane, Abdiwali Mohamed Ahmed, Mohamed Mustaf Ahmed

“…This study leverages machine learning (ML) algorithms and Shapley Additive extensions (SHAP) to identify key predictors of fertility preferences among reproductive-aged women in Somalia. …”
Get full text

On nonlinear coupled differential system for heat transfer in magnetized enclosure with T-shaped baffle by using machine learning by Khalil Ur Rehman, Wasfi Shatanawi, Lok Yian Yian

Get full text

A novel method to predict white blood cells after kidney transplantation based on machine learning by Songping He, Xiangxi Li, Zunyuan Zhao, Bin Li, Xin Tan, Hui Guo, Yanyan Chen, Xia Lu

Get full text

Predicting diabetic peripheral neuropathy through advanced plantar pressure analysis: a machine learning approach by Mehewish Musheer Sheikh, Mamatha Balachandra, Narendra V. G., Arun G. Maiya

Get full text

Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects by Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das, Md. Sunzidul Islam, Jong-Hoon Kim

“…Automatic scene generation is an essential area of research with applications in robotics, recreation, visual representation, training and simulation, education, and more. This survey provides a comprehensive review of the current state-of-the-arts in automatic scene generation, focusing on techniques that leverage machine learning, deep learning, embedded systems, and natural language processing (NLP). …”
Get full text

Safeguarding against Cyber Threats: Machine Learning-Based Approaches for Real-Time Fraud Detection and Prevention by Vikas R. Shetty, Pooja R., Rashmi Laxmikant Malghan

Get full text

Opinion Mining and Perceptions of Self-Determination in Videoconference Classrooms Using Machine Learning and Multidimensional Sentiment Frameworks by Bosede Iyiade Edwards

“…In the mixed method approach, Azure Machine Learning's (AML) three-category sentiment analysis as a quantitative approach is enhanced by a multidimensional sentiment model as a qualitative approach to analyse learner feedback. …”
Get full text

Hybrid machine learning and regression framework for automated phase classification and quantification in SEM images of commercial steels by Pavan Hiremath, Krishnamurthy D. Ambiger, Shilpa Suresh, Ranjan Kumar Ghadai, Ramakrishna Vikas Sadanand, G. Divya Deepak

Get full text

A Systematic Review on Intelligent Prediction of Inorganic Building Materials Performance by Mengru Li, Zhenya Zhang, Xianyi Zeng, Zhenglei He

Get full text

Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

Get full text

Efficiently charting the space of mixed vacancy-ordered perovskites by machine-learning encoded atomic-site information by Fan Zhang, Li Fu, Weiwei Gao, Peihong Zhang, Jijun Zhao

Get full text

Type 2 diabetes risk prediction using glycemic control Metrics: A machine learning approach by Radwan Qasrawi, Suliman Thwib, Ghada Issa, Razan Abu Ghoush, Malak Amro

“…This study aimed to develop a personalized T2DM risk prediction model using machine learning (ML), integrating clinical, behavioral, and dietary data, including glycemic index (GI) and glycemic load (GL) derived from actual food and recipe intake. …”
Get full text

A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

“…The growing need for data-driven early detection systems has encouraged the adoption of technologies such as machine learning (ML) to more effectively predict stunting prevalence. …”
Get full text

Investigating factors influencing quality of life in thyroid eye disease: insight from machine learning approaches by Haiyang Zhang, Shuo Wu, Lehan Yang, Chengjing Fan, Huifang Chen, Hui Wang, Tianyi Zhu, Yinwei Li, Jing Sun, Xuefei Song, Huifang Zhou, Terry J Smith, Xianqun Fan

Get full text

Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms. by Alemu Birara Zemariam, Biruk Beletew Abate, Addis Wondmagegn Alamaw, Eyob Shitie Lake, Gizachew Yilak, Mulat Ayele, Befkad Derese Tilahun, Habtamu Setegn Ngusie

“…Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of stunting among adolescent girls in Ethiopia.…”
Get full text

Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning by Xiaojie Li, Chunliang Jiang, Qingyan Xie, Huiquan Wang, Jiameng Xu, Guanjun Liu, Panpan Chang, Guang Zhang

Get full text