Automated Diagnosis of Heart Valve Diseases from Phonocardiogram Signals using Deep Learning

Simple item page
dc.contributor.authorDas, Samarjeet
dc.date.accessioned2024-12-05T05:55:31Z
dc.date.available2024-12-05T05:55:31Z
dc.date.issued2023
dc.descriptionSupervisor: Dandapat, Samarendra
dc.description.abstractHeart valve diseases (HVDs) are the primary causes of mortality in developing and underdeveloped countries. Early detection of HVDs is essential to avoid lethal heart diseases due to the disease’s progression. Phonocardiogram (PCG) signal provides a non-invasive and cost-effective tool that helps with the preliminary diagnosis of HVDs. However, the raw PCG signals are often susceptible to noise and artifacts. It degrades the signal quality and makes it challenging to diagnose HVDs manually. Furthermore, the wide variabilities in the PCG morphologies due to HVDs exhibit manual examination, often subjective and prone to human error. To address the above challenges, this dissertation focuses on developing automated deep-learning methods for diagnosing HVDs.
dc.identifier.otherROLL NO.176102005
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/2693
dc.language.isoen_US
dc.relation.ispartofseriesTH-3224
dc.titleAutomated Diagnosis of Heart Valve Diseases from Phonocardiogram Signals using Deep Learning
dc.typeThesis
Files
Original bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
Abstract-TH-3224_176102005.pdf
Size:
53.18 KB
Format:
Adobe Portable Document Format
Description:
ABSTRACT
Download
No Thumbnail Available
Name:
TH-3224_176102005.pdf
Size:
5.9 MB
Format:
Adobe Portable Document Format
Description:
THESIS
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
PhD Theses (Electronics and Electrical Engineering)