EXPLAINABLE AI FOR COLON POLYPS DETECTION

Artificial intelligence (AI) has rapidly developed over the past few decades and was considered to have a huge effect on all forms of technologies and everyday life. Due to the large volume of data, the usage of AI in healthcare system, has been increasing rapidly. Different AI techniques have be...

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Main Author: Ramli, Nur Iman Athilah
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.23033 /
Published: Universiti Teknologi PETRONAS 2021
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access: http://utpedia.utp.edu.my/23033/1/EE102_24600_Nur%20Iman%20Athilah%20Binti%20Ramli.pdf
http://utpedia.utp.edu.my/23033/
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spelling utp-utpedia.230332022-03-11T04:18:25Z http://utpedia.utp.edu.my/23033/ EXPLAINABLE AI FOR COLON POLYPS DETECTION Ramli, Nur Iman Athilah TK Electrical engineering. Electronics Nuclear engineering Artificial intelligence (AI) has rapidly developed over the past few decades and was considered to have a huge effect on all forms of technologies and everyday life. Due to the large volume of data, the usage of AI in healthcare system, has been increasing rapidly. Different AI techniques have been used in medical imaging, including, machine learning and the deep learning technique which is convolutional neural network (CNN) which have helped doctors identify diseases accurately and assess effective care for them. The use and processing of a large number of the digital images and a lot of medical records over a period of time has contributed to the development of big data. The interest in applying computer-aided diagnosis (CAD) and artificial intelligence (AI) to endoscopic evaluation in the gastrointestinal tract has been revived by recent developments in computing power, coupled with rapid growth in the quantity and availability of data. However, regulatory impediments that need to be implement before applying CAD in routine clinical practise because the complexity of AI driven clinical decision-making, which is generally regarded as a ' black box.' And as such, this study aims to create an explainable AI-based CAD method to help endoscopists distinguish polyps during endoscopy, which can justify their decisions using classification rules. Universiti Teknologi PETRONAS 2021-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/23033/1/EE102_24600_Nur%20Iman%20Athilah%20Binti%20Ramli.pdf Ramli, Nur Iman Athilah (2021) EXPLAINABLE AI FOR COLON POLYPS DETECTION. Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ramli, Nur Iman Athilah
EXPLAINABLE AI FOR COLON POLYPS DETECTION
description Artificial intelligence (AI) has rapidly developed over the past few decades and was considered to have a huge effect on all forms of technologies and everyday life. Due to the large volume of data, the usage of AI in healthcare system, has been increasing rapidly. Different AI techniques have been used in medical imaging, including, machine learning and the deep learning technique which is convolutional neural network (CNN) which have helped doctors identify diseases accurately and assess effective care for them. The use and processing of a large number of the digital images and a lot of medical records over a period of time has contributed to the development of big data. The interest in applying computer-aided diagnosis (CAD) and artificial intelligence (AI) to endoscopic evaluation in the gastrointestinal tract has been revived by recent developments in computing power, coupled with rapid growth in the quantity and availability of data. However, regulatory impediments that need to be implement before applying CAD in routine clinical practise because the complexity of AI driven clinical decision-making, which is generally regarded as a ' black box.' And as such, this study aims to create an explainable AI-based CAD method to help endoscopists distinguish polyps during endoscopy, which can justify their decisions using classification rules.
format Final Year Project
author Ramli, Nur Iman Athilah
author_sort Ramli, Nur Iman Athilah
title EXPLAINABLE AI FOR COLON POLYPS DETECTION
title_short EXPLAINABLE AI FOR COLON POLYPS DETECTION
title_full EXPLAINABLE AI FOR COLON POLYPS DETECTION
title_fullStr EXPLAINABLE AI FOR COLON POLYPS DETECTION
title_full_unstemmed EXPLAINABLE AI FOR COLON POLYPS DETECTION
title_sort explainable ai for colon polyps detection
publisher Universiti Teknologi PETRONAS
publishDate 2021
url http://utpedia.utp.edu.my/23033/1/EE102_24600_Nur%20Iman%20Athilah%20Binti%20Ramli.pdf
http://utpedia.utp.edu.my/23033/
_version_ 1741195897783451648
score 11.62408

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