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

The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...

Wearables, Mobile Health (m-Health), Real-Time Monitoring Share and Cite: Alqarni, A. (2025) Analysis of Decision Support ...

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 ...

WS/ ├── cancer_diagnosis.py # Main backend analysis and model training ├── app.py # Streamlit frontend application ├── launch.bat # Windows launcher script ├── launch.sh # Linux/Mac launcher script ...

Background: This study aimed to evaluate the predictive utility of routine hematological, inflammatory, and metabolic markers for bacteremia and to compare the classification performance of logistic ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

TREM-1 upregulation as a potential predictive immune biomarker of pathologic complete response (pCR) in patients (pts) with triple-negative breast cancer (TNBC) receiving neoadjuvant therapy (NAT).

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...