openheart.bmj

Risk prediction modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: leveraging machine learning

Background Preprocedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and benchmarking hospital performance. This study ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Moderne Expands Agent Tools Platform with Python Support for Intelligent, Deterministic Software Transformation

Moderne today announced Python language support across its Agent Tools platform, expanding the infrastructure organizations ...
Visual Studio Magazine

Decision Tree Regression from Scratch Without Pointers or Recursion Using C#

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
UroToday

Decision tree models combining Bi-parametric vesical imaging reporting and data system and apparent diffusion coefficient metrics for predicting muscle-invasive bladder cancer.

To compare whole-lesion apparent diffusion coefficient (ADC) histogram analysis with representative ADC value for assessing muscle invasion in bladder cancer, and to build a decision tree model that ...
IEEE

Application of decision tree model in policy effect evaluation of green electricity market

Abstract: In recent years, the green electricity market has become a significant focus due to the increasing emphasis on sustainable development and carbon emission reduction. However, evaluating the ...
GitHub

decision-tree-classifier

ML powered system that predicts most suitable crop using ensemble(hard voting) of Decision Tree, Random Forest, and Gradient Boosting models implemented from scratch ...
Scientific Research Publishing

Application of Precise Loan Qualification Identification Based on K-Means and Decision Tree Model from the Perspective of Consumer Behavior in Universities ()

From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models. A ...
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 ...
marktechpost

How to Build an Agentic Decision-Tree RAG System with Intelligent Query Routing, Self-Checking, and Iterative Refinement?

In this tutorial, we build an advanced Agentic Retrieval-Augmented Generation (RAG) system that goes beyond simple question answering. We design it to intelligently route queries to the right ...
ahajournals.org

Mechanical Thrombectomy for Patients with Large Core Ischemic Strokes—An International Cost‐Effectiveness Analysis

Recent trials demonstrate mechanical thrombectomy (MT) benefits patients with large core infarcts. This study assesses the cost‐effectiveness of MT in this population across a range of international ...