Given the rapidly evolving landscape of Artificial Intelligence, one of the biggest hurdles tech leaders often come across is ...
Abstract: The research paper describes a software-based medical risk analysis system which predicts heart disease and diabetes by analyzing patient health information collected without sensors or ...
Epithelial ovarian cancer (EOC) has a high rate of incidence and mortality, seriously threatening women’s health. Artificial intelligence (AI) possesses functions such as image recognition, data ...
Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
A production-ready machine learning service for intent classification built with Python Flask and deployed on Amazon EKS (Elastic Kubernetes Service). This project demonstrates best practices for ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Objectives: To develop and validate machine learning models to predict levodopa responsiveness of tremor in Parkinson’s disease (PD) patients. Methods: A total of 197 PD tremor patients underwent ...
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