A team of scientists at The University of Texas Medical Branch (UTMB), led by Nikos Vasilakis, Ph.D., and Peter McCaffrey, MD ...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...

Brookfield Corporation (NYSE: BN) has enriched its investors over the years. The global investment management firm has delivered a 19% annualized return over the last 30 years. That has absolutely ...

Across the country, algorithms are shaping decisions about who gets hired, who advances, and who is filtered out, often before a hiring manager ever takes a closer look. What began as an efficiency ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

Abstract: Technical Debt (TD) refers to the long-term costs of suboptimal choices made for short-term gains. Algorithm Debt (AD), a type of TD, refers to the sub-optimal implementation of an algorithm ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.