Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...
Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a ...
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
Abstract: By use of recurrence plots (RP) and cross recurrence quantification analysis (CRQA) model nonlinear correlation in stocks used Cross Recurrence Plot (CRP) data converted into a time-series ...
A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Clara Matos discusses the journey of shipping AI-powered healthcare products at Sword Health. She explains how to implement ...
Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...
Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...
Abstract: Software projects often fail due to poor effort estimation, which can lead to issues such as wasted time and resources. Developing software requires significant time, money, and skilled ...
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