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Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future

Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future
Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future

Over the years, many clinical and engineering methods have been adapted for testing and screening for the presence of diseases. The most commonly used methods for diagnosis and analysis are computed tomography (CT) and X-ray imaging. Manual interpretation of these images is the current gold standard but can be subject to human error, is tedious, and is time-consuming. To improve efficiency and productivity, incorporating machine learning (ML) and deep learning (DL) algorithms could expedite the process. This article aims to review the role of artificial intelligence (AI) and its contribution to data science as well as various learning algorithms in radiology. We will analyze and explore the potential applications in image interpretation and radiological advances for AI. Furthermore, we will discuss the usage, methodology implemented, future of these concepts in radiology, and their limitations and challenges.

artificial intelligence, data science, data science in radiology, deep learning, machine learning, machine learning in radiology, radiology
1756-2872
Hameed, B M Zeeshan
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Prerepa, Gayathri
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Patil, Vathsala
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Shekhar, Pranav
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Zahid Raza, Syed
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Karimi, Hadis
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Paul, Rahul
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Naik, Nithesh
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Modi, Sachin
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Vigneswaran, Ganesh
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Prasad Rai, Bhavan
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Chłosta, Piotr
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Somani, Bhaskar K
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Hameed, B M Zeeshan
b0e68d88-bb17-4c75-8a65-64e0ed509560
Prerepa, Gayathri
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Patil, Vathsala
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Shekhar, Pranav
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Zahid Raza, Syed
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Karimi, Hadis
558e0336-7d78-4405-9b8c-5f0c7e310f73
Paul, Rahul
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Naik, Nithesh
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Modi, Sachin
caef086a-dda5-418a-ada8-fc042e6e0b18
Vigneswaran, Ganesh
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Prasad Rai, Bhavan
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Chłosta, Piotr
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Somani, Bhaskar K
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Hameed, B M Zeeshan, Prerepa, Gayathri, Patil, Vathsala, Shekhar, Pranav, Zahid Raza, Syed, Karimi, Hadis, Paul, Rahul, Naik, Nithesh, Modi, Sachin, Vigneswaran, Ganesh, Prasad Rai, Bhavan, Chłosta, Piotr and Somani, Bhaskar K (2021) Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future. Therapeutic Advances in Urology, 13. (doi:10.1177/17562872211044880).

Record type: Review

Abstract

Over the years, many clinical and engineering methods have been adapted for testing and screening for the presence of diseases. The most commonly used methods for diagnosis and analysis are computed tomography (CT) and X-ray imaging. Manual interpretation of these images is the current gold standard but can be subject to human error, is tedious, and is time-consuming. To improve efficiency and productivity, incorporating machine learning (ML) and deep learning (DL) algorithms could expedite the process. This article aims to review the role of artificial intelligence (AI) and its contribution to data science as well as various learning algorithms in radiology. We will analyze and explore the potential applications in image interpretation and radiological advances for AI. Furthermore, we will discuss the usage, methodology implemented, future of these concepts in radiology, and their limitations and challenges.

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17562872211044880 - Version of Record
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More information

Accepted/In Press date: 21 August 2021
e-pub ahead of print date: 30 September 2021
Published date: September 2021
Keywords: artificial intelligence, data science, data science in radiology, deep learning, machine learning, machine learning in radiology, radiology

Identifiers

Local EPrints ID: 452974
URI: http://eprints.soton.ac.uk/id/eprint/452974
ISSN: 1756-2872
PURE UUID: f7b5d414-d366-4b7c-aac1-7432b5494434
ORCID for Ganesh Vigneswaran: ORCID iD orcid.org/0000-0002-4115-428X

Catalogue record

Date deposited: 07 Jan 2022 12:04
Last modified: 02 Jul 2022 02:09

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Contributors

Author: B M Zeeshan Hameed
Author: Gayathri Prerepa
Author: Vathsala Patil
Author: Pranav Shekhar
Author: Syed Zahid Raza
Author: Hadis Karimi
Author: Rahul Paul
Author: Nithesh Naik
Author: Sachin Modi
Author: Bhavan Prasad Rai
Author: Piotr Chłosta

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