Open Heart

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
The BMJ

When I use a word . . . Artificial intelligence—predicting and detecting adverse drug reactions

The Law of Mass action predicts that all adverse drug reactions are related to the concentration of the drug at the site of ...
Ecommerce Fastlane

What Are AI Algorithms? Types of AI Algorithms + Use Cases

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...
IEEE

Reducing Unnecessary Handovers Using Logistic Regression in 5G Networks

Abstract: The evolution of wireless communication has brought great benefits to society, such as multi-connectivity, increased connection speed, low latency, and elevated throughput. However, it has ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...
Visual Studio Magazine

Implementing k-Nearest Neighbors Regression Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...
IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
Frontiers

Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...
Hosted on MSN

What Is Linear Regression In Machine Learning ? Understand With Examples

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...