The application and predictive value of the weight-adjusted-waist index in BC prevalence assessment: a comprehensive statistical and machine learning analysis using NHANES data by Wenjing Wang, Biao Wu, Jian Li, Yibiao Shang, Mengting Liu, Qi Fang, Han Zhang, Xiang Li, Dongdi Wu

“…Multicollinearity was addressed using variance inflation factor diagnostics. Machine learning methods, including random forest and LASSO regression, were employed for variable selection and model comparison. …”
Get full text

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning by Jun Wang, Yuan Cong, Bo Tang, Juan Liu, Ke Pu

“…We performed an integrative analysis of multi-omics data from 274 CRC patients to investigate the impact of gut microbiota composition on prognosis, identify novel subtypes, and develop a machine learning-based prognostic model. …”
Get full text

Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…Abstract Malaria remains a critical global health challenge requiring innovative diagnostic approaches. Machine learning offers promising solutions for automated detection, but systematic algorithm comparison using clinically validated data remains limited. …”
Get full text

GeaGrow: a mobile tool for soil nutrient prediction and fertilizer optimization using artificial neural networks by Olusegun Folorunso, Oluwafolake Ojo, Mutiu Busari, Muftau Adebayo, Joshua Adejumobi, Daniel Folorunso, Femi Ayo, Orobosade Alabi, Olusola Olabanjo

Subjects: Get full text

Modeling Population Mobility Flows: A Hybrid Approach Integrating a Gravity Model and Machine Learning by Jingjing Liu, Lei Xu, Le Ma, Nengcheng Chen

“…Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationships between origin and destination characteristics and migration. …”
Get full text

Realizing the potential of Internet of Things (IoT) in Industrial applications by Bharat Rathi, S. Thapaswi, Meghana Kambhampati, Vineet Jain, P. Akshay, Trilok Nath Pandey, Sunil Kumar Pradhan

Subjects: Get full text

Characteristic genes and immune infiltration analysis of gastric cancer based on bioinformatics analysis and machine learning by Chengwei Xia, Yini Liu, Xin Qing

Get full text

A Comparative Analysis of Machine Learning Algorithms for Classification of Diabetes Utilizing Confusion Matrix Analysis by Maad M. Mijwil, Mohammad Aljanabi

Get full text

With eyes of a machine: A three-step guide for applying machine learning to visual content analysis in social research by Anna Helene Kvist Møller, Massimo Airoldi

Get full text

Predicting salinity levels in the Mekong delta (Viet Nam): analysis of machine learning and deep learning models by Phong Nguyen Duc, Thang Tang Duc, Giap Pham Van, Hoat Nguyen Van, Tuan Tran Minh

Get full text

Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances by V. Indragandhi, R. Senthil Kumar, R. Saranya

“…Monitoring and predicting Power Quality (PQ) is crucial for quickly minimizing risk, protecting induction machines (IMs), and increasing productivity. This paper proposes an electromechanical analytical framework for IM working with various PQ disturbances based on machine learning (ML). …”
Get full text

Unveiling Public Sentiments in Crisis: The EHDSAF Approach to Dark Social Media Data during the 2010 Pakistan Flood by Fazal Tariq, Muhammad Tufail, Taj Rehman

Subjects: “…Dark Data, Big Data, Machine Learning, Deep Learning, Sentiment Analysis, NLP, VADER.…”
Get full text

A Hybrid Deep Learning-Machine Learning Stacking Model for Yemeni Arabic Dialect Sentiment Analysis by Alaa Abdulkareem Hameed Brihi, Mossa Ghurab

“…We systematically evaluate sentiment analysis approaches, including lexicon-based, machine learning, deep learning, and hybrid, in terms of user sentiment regarding Yemeni telecom services. …”
Get full text

A data-driven framework for predicting solar rooftop adoption in Germany based on open-source data by Kaan Duran, Antonello Monti

Get full text

Machine learning and deep learning in glioblastoma: a systematic review and meta-analysis of diagnosis, prognosis, and treatment by Hadja Fatima Tbahriti, Ali Boukadoum, Meriem Benbernou, Mohamed Belhocine

“…Results The performance of the machine and deep learning models was strong across different clinical tasks. …”
Get full text

Improving CNN predictive accuracy in COVID-19 health analytics by Tae-hoon Kim, Asadi Srinivasulu, Ravikumar Chinthaginjala, Dhakshayani J, Xin Zhao, Safia Obaidur Rab, Sivarama Prasad Tera

Get full text

Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases by Ana Gutiérrez, Jose Aguilar, Ana Ortega, Edwin Montoya

Subjects: Get full text

Development of digital twin of CNC unit based on machine learning methods by Yu. G. Kabaldin, D. A. Shatagin, M. S. Anosov, A. M. Kuzmishina

“…Machine learning methods valid for the implementation of the above tasks are evaluated. …”
Get full text

Cold-start visualization recommendation driven by large language models for ocean data analysis by Xin Li, Jixiu Liao, Wen Liu, Yu Miao, Leyu Wang, Shuqing Sun

Get full text

Guest Editorial: Smart cities 2.0: How Artificial Intelligence and Internet of Things are transforming urban living by Zheng‐Yi Chai, Syed Attique Shah, Dirk Draheim, Sufian Hameed, Muhammad Mazhar Ullah Rathore

Subjects: Get full text