[PDF][PDF] Involving machine learning techniques in heart disease diagnosis: a performance analysis

BS Shukur, MM Mijwil - International Journal of Electrical and …, 2023 - academia.edu
Artificial intelligence is a science that is growing at a tremendous speed every day and has
become an essential part of many domains, including the medical domain. Therefore …

Creating alert messages based on wild animal activity detection using hybrid deep neural networks

B Natarajan, R Elakkiya, R Bhuvaneswari… - IEEE …, 2023 - ieeexplore.ieee.org
The issue of animal attacks is increasingly concerning for rural populations and forestry
workers. To track the movement of wild animals, surveillance cameras and drones are often …

[HTML][HTML] A hybrid deep neural net learning model for predicting Coronary Heart Disease using Randomized Search Cross-Validation Optimization

N Sharma, L Malviya, A Jadhav, P Lalwani - Decision Analytics Journal, 2023 - Elsevier
Abstract Coronary Heart Disease (CHD) is a life-threatening public health problem. Many
chronic CHDs and health risks can be avoided, reversed, and reduced with proper risk …

Chronic Diseases Prediction Using Machine Learning With Data Preprocessing Handling: A Critical Review

NG Ramadhan, W Maharani, AA Gozali - IEEE Access, 2024 - ieeexplore.ieee.org
According to the World Health Organization (WHO), some chronic diseases such as
diabetes mellitus, stroke, cancer, cardiac vascular, kidney failure, and hypertension are …

Text Summarization for Big Data Analytics: A Comprehensive Review of GPT 2 and BERT Approaches

G Bharathi Mohan, R Prasanna Kumar… - Data Analytics for …, 2023 - Springer
The goal of approaches to automatic text summarization is to construct summaries while
extracting the essential information from one or more input texts. Large models could be …

Ipl data analysis and visualization for team selection and profit strategy

G Saranya, A Swaminathan… - 2023 7th …, 2023 - ieeexplore.ieee.org
Day by day, the role of data science and machine learning in cricket is increasing due to the
large amount of data generated from a single player on a whole line. The field of data …

Forecasting Coronary Heart Disease Risk with a 2-Step Hybrid Ensemble Learning Method and Forward Feature Selection Algorithm

SC Patra, BU Maheswari, PB Pati - IEEE Access, 2023 - ieeexplore.ieee.org
Detecting cardiovascular irregularities in a timely manner is crucial for preventing any fatal
risks. This research aims to devise an efficient forecasting algorithm for the timely prognosis …

[PDF][PDF] Predictive Analytics of Heart Disease Presence with Feature Importance Based on Machine Learning Algorithms

NR Kolukula, PN Pothineni, VMK Chinta… - Indonesian Journal of …, 2023 - researchgate.net
Heart failure disease is a complex clinical issue which has more impact on life of human
begins. Hospitals and cardiac centers frequently employ electrocardiogram (ECG) tool to …

A More Flexible and Robust Feature Selection Algorithm

T Tu, Y Su, Y Tang, W Tan, S Ren - IEEE Access, 2023 - ieeexplore.ieee.org
With the increasing amount of real data, the challenges of large-scale model operations as
well as poor generalization capacity, making selection of an appropriate feature set a …

Stacking Ensemble Model for Celestial Object Classification: Galaxies, Stars and Quasars

S Sudharson, R Annamalai, AA Reddy… - … Conference on Image …, 2023 - ieeexplore.ieee.org
In the field of astronomy, it is essential to classify celestial objects like stars, galaxies, and
quasars based on their spectral characteristics. This spectral data provides valuable …