Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Morning Overview on MSN

Scientists build a ‘periodic table’ for AI models

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...
GitHub

Statistical Foundation of Data Science

This repository contains comprehensive implementations and solutions for statistical analysis, data science methodologies, and computational mathematics assignments. Each assignment demonstrates ...
Frontiers

Clinical decision system for renal cell carcinoma integrating interpretable machine learning algorithms

Background: Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and ...
Visual Studio Magazine

Decision Tree Regression from Scratch with Pointers Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...
Frontiers

Risk factors for hematuria during indwelling urinary catheterization in acute myocardial infarction: a comparative analysis using logistic regression and decision tree

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 ...
Scientific Research Publishing

The Math Works Inc (2024) Stepwise Regression Toolbox Documentation. The MathWorks Inc.

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...
SciELO

The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting

This cross-sectional study investigated SLD-related variables using decision tree regression in apparently healthy adults. Participants were consecutively recruited from the Health Promotion and Check ...
C&EN

From Reaction Stoichiometry to Life Cycle Assessment: Decision Tree-Based Estimation Tool

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...
IEEE

Predicting Medical Claim Denial Using Logistic Regression and Decision Tree Algorithm

Abstract: This study utilizes decision tree and logistic regression models to explore the factors contributing to medical claim denials and identify areas for improvement. We adapt undersampling ...