Machine learning approach for ECG analysis and predicting different heart diseases

Machine learning approach for ECG analysis and predicting different heart diseases

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Bibliografski detalji
Glavni autori:	Tithi, Sushmita Roy, Aktar, Afifa, Aleem, Fahimul
Daljnji autori:	Chakrabarty, Amitabha
Format:	Disertacija
Jezik:	English
Izdano:	BRAC University 2019
Teme:	Machine learning ECG Heart diseases Diseases > Early detection. Medical informatics. Artificial intelligence. Machine learning.
Online pristup:	http://hdl.handle.net/10361/11409

Similar Items

Heart disease prediction using machine learning algorithms
od: Ali, Musfiq, i dr.
Izdano: (2019)

Comparison of machine learning techniques to predict cardiovascular disease
od: Jaber, Mir Mohammad, i dr.
Izdano: (2019)

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
od: Oishi, Fayza Rezwana, i dr.
Izdano: (2020)

Heart disease prediction system
od: Amit, Tayab Al Azad, i dr.
Izdano: (2022)

Heart disease prediction using techniques of classification in machine learning
od: Afrose, Sadia, i dr.
Izdano: (2021)

Comparative analysis of machine learning models for the prediction of asthma disease among the cardiovascular disease patients
od: Jahan, Asif
Izdano: (2024)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
od: Ferdous, Md.Rubaiat, i dr.
Izdano: (2024)

Determining fatal heart failure risks in patients diagnosed with chronic kidney disease: a machine learning approach
od: Haque, Adiba, i dr.
Izdano: (2022)

Enhancing Monkeypox diagnosis: a machine learning approach for skin lession classification
od: Nazmee, Namirah, i dr.
Izdano: (2024)

Prediction of coronary heart diseases using supervised machine learning algorithms
od: Salam, Nazia Binte, i dr.
Izdano: (2023)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
od: Shawan, Naveed Rahman, i dr.
Izdano: (2019)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
od: Rafat, Md. Tasbi, i dr.
Izdano: (2023)

Predicting obesity: a comparative analysis of machine learning models incorporating different features
od: Rahman, Md.Sakibur, i dr.
Izdano: (2023)

Predicting climate induced floods using machine learning
od: Saleh, Chowdhury Nafis, i dr.
Izdano: (2022)

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
od: Bhuiyan, Mahdi Hasan, i dr.
Izdano: (2024)

Real time performance analysis on DDoS attack detection using machine learning
od: Suvra, Debashis Kar, i dr.
Izdano: (2021)

Smart biomedical device to predict lung diseases, COVID-19 and diabetes by using machine learning algorithms
od: Hossain, Ashraful, i dr.
Izdano: (2024)

Heart attack prediction using machine learning and XAI
od: Ahsan, Mumtahina
Izdano: (2023)

An implementation and analysis of deep learning models for the detection of wheat diseases
od: Zubair, Ahmad, i dr.
Izdano: (2024)

Crop prediction based on geographical and climatic data using machine learning and deep learning
od: Alif, Al Amin, i dr.
Izdano: (2019)

Developing a machine learning based prognostic model and a supporting web-based application for predicting the possibility of early diabetes and diabetic kidney disease
od: Amin, M.M. Shahriar, i dr.
Izdano: (2021)

Deep learning based arrhythmia classification on low-cost and low-compute MCU
od: Zishan, Md Abu Obaida, i dr.
Izdano: (2023)

Exploring machine learning techniques for symptom-based detection of livestock diseases
od: Niloy, Mahir Ahmed, i dr.
Izdano: (2024)

Alumni opportunities using machine learning
od: Siaum, Arshif Sharlimin, i dr.
Izdano: (2019)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
od: Ifty, Md. Hasin Sarwar, i dr.
Izdano: (2024)

Fault detection in waste water treatment plant using statistical analysis & machine learning
od: Haque, Md. Ezazul, i dr.
Izdano: (2019)

Machine learning approach for improving decision support in ICU
od: Siddiquee, Mohib Billah, i dr.
Izdano: (2019)

Effectiveness of data mining in predicting heart diseases
od: Afrin, Shahria, i dr.
Izdano: (2018)

Plant disease detection using convolutional neural network
od: Hossain, Mohammad Shifat, i dr.
Izdano: (2021)

A machine learning approach to credit default prediction and Individual credit scoring
od: Rahman, Md. Jaber, i dr.
Izdano: (2018)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
od: Radiah, Faiza, i dr.
Izdano: (2024)

Cardiovascular disease prediction model using Machine Learning Algorithm
od: Arefin Mirdha, MD Shamsul
Izdano: (2023)

Predicting depression in Bangladeshi undergraduates using machine learning
od: Choudhury, Ahnaf Atef, i dr.
Izdano: (2019)

Machine learning as an indicator for breast cancer prediction
od: Shadman, Tahsin Mohammed, i dr.
Izdano: (2019)

Application of machine learning in credit risk assessment: a prelude to smart banking
od: Dhruba, Mir Ishrak Maheer, i dr.
Izdano: (2019)

A semi-supervised federated learning approach leveraging pseudo-labeling for Knee Osteoarthritis severity detection
od: Rifat, Rakib Hossain
Izdano: (2024)

A hybrid rumor detection model derived from a comparative study of supervised approaches
od: Aothoi, Mehzabin Sadat, i dr.
Izdano: (2023)

Using deep learning algorithms to detect violent activities
od: Ammar, S.M. Rojin, i dr.
Izdano: (2019)

Real-time foul detection in football matches using machine learning techniques
od: Siddiqui, Bishal Sadi, i dr.
Izdano: (2024)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
od: Rahee, Arnob, i dr.
Izdano: (2021)