Bayesian Model Prediction for Lung Cancer Survival Based on Demographic and Laboratory Results: A retrospective analysis.
Aim: To examine the likelihood of predicting lung cancer survival versus death using Bayesian model based on demographic and laboratory data. Methods: A predictive design using electronic health records from 2012 to 2023 was implemented. IBM SPSS Statistics version 29.0 was used for data descriptive analysis and prediction models were built using ...
By Islam Bani Mohammad, Muayyad Ahmad
Artificial intelligence and big data applications in chronic disease management: clinical outcomes, challenges, and future directions
Aim: To synthesize applications of Artificial Intelligence (AI) and big data in chronic disease management, evaluate clinical and economic outcomes, challenges, and future directions. Methods: A comprehensive search was conducted across PubMed, Scopus, Web of Science, IEEE Xplore, and CINAHL for studies published between 2015-2025, following the P...
By Sana'a Abu-Qbeitah, Muayyad Ahmad
A systematic evaluation of big data-driven colorectal cancer studies
Aim To assess machine-learning models, their methodological quality, compare their performance, and highlight their limitations.Methods The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations were applied. Electronic databases Science Direct, MEDLINE through (PubMed, Google Scholar), EBSCO, ERIC, and CINAHL w...
By Eslam Bani Mohammad, Muayyad Ahmad