Objective: To understand patient portal engagement stratified by patient characteristics among adults 50 years and older with at least 1 common chronic medical condition using electronic health ...

Abstract: Data analytics can help drive decision-making and improve patient outcomes in healthcare. But of course, healthcare data is complex, and the process to access & analyze it can be slow. Here, ...

Understanding the derivative of the cost function is key to mastering logistic regression. Learn how gradient descent updates weights efficiently in machine learning. #MachineLearning ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...

Objective: This study aimed to systematically identify risk factors for urinary catheter-related hematuria in patients with acute myocardial infarction (AMI). By integrating logistic regression and ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

This repository contains a mockup full-stack application that fetches a wide range of U.S. economic data from the FRED API, vectorizes it using Pinecone, and provides a chatbot interface for querying ...

Background: This study aimed to evaluate the predictive utility of routine hematological, inflammatory, and metabolic markers for bacteremia and to compare the classification performance of logistic ...

What if you could transform the way you analyze data in just 12 minutes? Picture this: a mountain of raw numbers and spreadsheets that once felt overwhelming now becomes a treasure trove of actionable ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...