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 .

Reliable fault diagnostics in gearboxes is of great importance to industries to improve production quality and reduce maintenance costs. In this paper, an improved evolving fuzzy (iEF) technique is ...

Objective: This study aimed to develop and evaluate a machine learning (ML)–based algorithm to predict whether an initial vancomycin dose falls within the therapeutic range of the 24-hour area under ...

Traditionally, the term “braindump” referred to someone taking an exam, memorizing the questions, and sharing them online for others to use. That practice is unethical and violates the ISC2 ...

We designed a model to predict the timing of gastrostomy requirement in ALS as indicated by 5% weight loss from diagnosis. We considered >5000 different prediction model configurations including ...

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