Given the rapidly evolving landscape of Artificial Intelligence, one of the biggest hurdles tech leaders often come across is ...

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 ...

Real-time intelligent connectivity is a necessity, yet telecommunications infrastructure—built for a different era—struggles to keep pace. As data traffic explodes and latency-sensitive applications ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

As artificial intelligence (AI) continues to revolutionize the economy, courts are increasingly being asked to determine whether AI models and algorithms can be protected as trade secrets. Yet case ...

Objective: To construct a prediction model for teicoplanin (TEIC) plasma concentrations through machine learning and deep learning techniques in patients with liver disease using real-world clinical ...

As health system executives explore the potential benefits of agentic AI, many see call centers as low hanging fruit to test out conversational AI. Calls centers are costly to run, are often short on ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

This research introduces a novel approach to uncovering structural variables in complex systems, reshaping how we model the unpredictable behaviour of the real world Connected puzzle pieces (Courtesy: ...

Pulmonary hypertension in CKD is frequently underdiagnosed due to nonspecific early symptoms and limited screening practices. A machine learning model using basic clinical data can predict PH risk, ...

In this tutorial, we explore LitServe, a lightweight and powerful serving framework that allows us to deploy machine learning models as APIs with minimal effort. We build and test multiple endpoints ...

A simple Flask application that can serve predictions machine learning model. Reads a pickled sklearn model into memory when the Flask app is started and returns predictions through the /predict ...