Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
GitHub

Hand-Drawn Shape Classifier

Objectives Create a custom dataset ("MyDoodles") by drawing directly on a digital canvas. Implement Perceptron and Logistic Regression algorithms from scratch (without PyTorch/TensorFlow). Verify the ...
EurekAlert!

Transforming acute exacerbations of chronic obstructivepulmonary disease (AECOPD) risk assessment: Amulti-algorithm machine learning approach for preciseclinical phenotyping

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...
Scientific Research Publishing

Binsawad, M. (2025). Enhanced Financial Fraud Detection Using an Adaptive Voted Perceptron Model with Optimized Learning and Error Reduction. Electronics, 14, Article 1875.

ABSTRACT: Over the past decade, financial fraud has emerged as a critical challenge in rural communities, where limited financial literacy, weak digital infrastructure, and social vulnerabilities make ...
Scientific Research Publishing

Nosratabadi, S., Ardabili, S., Lakner, Z., Mako, C. and Mosavi, A. (2021) Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS ...

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...
IEEE

Learning 3D Rotations from Point Cloud Data

Abstract: This paper presents a deep learning (DL) based method for 3D rotation prediction on point cloud data. The proposed approach utilizes a single graph convolutional layer to capture meaningful ...
Frontiers

Intelligent maneuver decision-making for UAVs using the TD3–LSTM reinforcement learning algorithm under uncertain information

Aiming to address the complexity and uncertainty of unmanned aerial vehicle (UAV) aerial confrontation, a twin delayed deep deterministic policy gradient (TD3)–long short-term memory (LSTM) ...
ahajournals.org

The Promise and Peril of Learning Algorithms and Predictive Models in Clinical Decision Support: Be Careful What You Train For

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical decision-making through the identification and ...