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Artif Intell Cancer. Jul 28, 2022; 3(3): 42-53
Published online Jul 28, 2022. doi: 10.35713/aic.v3.i3.42
Building and evaluating an artificial intelligence algorithm: A practical guide for practicing oncologists
Anupama Ramachandran, Deeksha Bhalla, Krithika Rangarajan, Raja Pramanik, Subhashis Banerjee, Chetan Arora
Anupama Ramachandran, Deeksha Bhalla, Department of Radiology, All India Institute of Medical Sciences, New Delhi 110029, India
Krithika Rangarajan, Department of Radiology, All India Institute of Medical Sciences New Delhi, New Delhi 110029, India
Krithika Rangarajan, School of Information Technology, Indian Institute of Technology, Delhi 110016, India
Raja Pramanik, Department of Medical Oncology, Dr. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences, New Delhi 110029, India
Subhashis Banerjee, Chetan Arora, Department of Computer Science, Indian Institute of Technology, Delhi 110016, India
Author contributions: Ramachandran A, Bhalla D, and Rangarajan K were involved in primary writing of the manuscript; Pramanik R gave inputs from a medical oncology perspective; Banerjee S and Arora C gave inputs from a computer science perspective.
Conflict-of-interest statement: All the authors have no conflict of interests to declare.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Krithika Rangarajan, MBBS, MD, Assistant Professor, Department of Radiology, All India Institute of Medical Sciences New Delhi, Ansari Nagar, New Delhi 110029, India. krithikarangarajan86@gmail.com
Received: February 14, 2022
Peer-review started: February 14, 2022
First decision: March 12, 2022
Revised: April 9, 2022
Accepted: July 13, 2022
Article in press: June 13, 2022
Published online: July 28, 2022
Core Tip

Core Tip: Designing projects and evaluating algorithms require a basic understanding of principles of machine learning. In addition, specific tasks have specific data requirements, annotation requirements, and applications. In this review, we describe the basic principles of machine learning, as well as explain various common tasks and their data requirements and applications in order to enable practicing oncologists to plan their own projects.