A SAS analysis project on cardiovascular disease data

This Project is based upon a CHDs (Cardiovascular Heart Diseases) research dataset which has over 3000 records and 16 attributes. Since, the target variable belongs to Categorical attribute, We built classification models for the future predictions of CHDs in patients considering the features.

INVESTIGATING THE ASSOCIATION BETWEEN POLYGENIC RISK SCORE OF ADIPOSE TISSUE FUNCTION AND CARDIOVASCULAR DISEASE

Code for MICCAI 2023 publication: SCOL: Supervised Contrastive Ordinal Loss for Abdominal Aortic Calcification Scoring on Vertebral Fracture Assessment Scans

This work classifies who different diseases leads to cardiovascular disease unknowing to the people of mid-age or more. And determines how accurate is testing data w.r.t. training data through linear regression , Machine Learning

Understanding the Molecular Interface of Cardiovascular Disease and COVID-19: A Data Science Approach

Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank

Proyecto que busca predecir enfermedades cardiovasculares en pacientes potenciales, analizando una serie de factores de la salud cardiaca de los mismos, a partir de la ayuda de machine learning vía tres clasificadores de aprendizaje supervisado.

Fall 2022 Bioengineering 298 Final Project: using protein networks to understand drug and disease mechanisms

Cardiovascular disease dataset analysis for LaCCAN/UFAL

This repo contains a Machine Learning-based methodology for the preliminary design of a risk calculator using medical tabular databases, combining the knowledge of different clinically validated cardiovascular risk calculators using Transfer Learning (TL).

The project consists in building a Transformer Encoder to predict deaths from cardiovascular diseases. An important part is to exploit missing values in order not to lose data information. Data augmentation is performed by adding missing values and noise to training records.

Detecting Heart disease in patients using svm

Developpement of a machine learning model (SVM classifier) for cardiovascular disease prediction. Deployed on a streamlit app.

Cardiovascular Disease Prediction on 19 Lifestyle Factors

Blake's Haas Capstone Project - Patient Readmissions Prediction

Projet d'analyse de données - Maladies cardiovasculaires- R

Ping Lab Intern Project, Summar, 2022: Mapping MeSH (ICD codes) to molecular mechanism through protein-protein co-occurance graph -toward high precission medicine