Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...

This book isn't enough to teach me a new skill, so I reached out to some Houston music friends Credit: Jesse Sendejas, Jr. I frequently write about music and my kids are in bands so I’m often asked if ...

In an environment defined by labor shortages, rising uptime expectations and pressure to improve overall equipment effectiveness (OEE), simple data collection is no longer enough. Modern manufacturers ...

Text-based depression estimation using natural language processing has emerged as a feasible approach for early mental health screening. However, most existing reviews often included studies with weak ...

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 ...

Gestational diabetes mellitus (GDM), a prevalent metabolic disorder associated with pregnancy, which often postpones intervention until after metabolic complications have developed. This study seeks ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

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Phoenix’s Musical Instrument Museum doesn’t just display exotic and unique music-making artifacts; it also showcases them in action. Inside its intimate 300-seat theater, the MIM hosts performances ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...