We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...

The hybrid model is emerging as the framework for trustworthy AI in test analytics. It retains traceability and supports ...

The CT-based whole-lung radiomic nomogram accurately identifies AECOPD and offers a robust tool for clinical diagnosis and treatment planning.

These questions come from my Udemy training and the certificationexams.pro website, resources that have helped many students pass the DP-100 certification. These are not DP-100 exam dumps or ...

Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .

The cohort was randomly divided into training and testing datasets in a 7:3 ratio, and multiple ML techniques were used to develop an algorithm for optimizing initial vancomycin dosing. The optimal ...

Community driven content discussing all aspects of software development from DevOps to design patterns. Study thoroughly, practice consistently, and gain hands-on experience with security tools, ...

Optimised machine learning for time-to-event prediction in healthcare applied to timing of gastrostomy in ALS: a multi-centre, retrospective model development and validation study Marcel Weinreich a, ...

As artificial intelligence (AI) becomes a fixture across a broad range of technological fields, AI technology continues to evolve at rapid rates.