Hospitals nationwide are facing intensifying staffing pressures, rising patient acuity and growing demands for more sustainable care delivery. At Cleveland-based University Hospitals, a new virtual ...

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical Deployment Study ...

NVIDIA's GPU memory swap technology aims to reduce costs and improve performance for deploying large language models by optimizing GPU utilization and minimizing latency. In a bid to address the ...

“To me, this technology is like moving to the cloud years ago—a prerequisite to doing a lot of the things we’ve been able to do since. And it’s the same with our Azure IoT Operations platform. It will ...

This project is designed to classify the sentiments of the real-time Tweets fetched via Twitter API. Implemented in an end-to-end manner deployed using Flask Framework in Heroku Platform(PAAS).

Electric trucks are a key part of the solution to decarbonize Canada’s freight sector. They reduce traffic-related air pollution, cut fuel and maintenance costs and offer a pathway to revive Ontario’s ...

Abstract: Crop diseases have a disproportionately large economic effect on farmers and threaten food security. Predictive Model for Crop Disease and Management System, which uses machine and deep ...

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 ...