Publication Name	Artificial Intelligence in Cancer
Manuscript ID	75772
Country	India

Received	2022-02-14 12:22
Peer-Review Started	2022-02-14 12:24
To Make the First Decision
Return for Revision	2022-03-12 02:35
Revised	2022-04-09 07:08
Second Decision	2022-06-06 03:23
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2022-06-17 22:49
Articles in Press	2022-06-17 22:49
Publication Fee Transferred
Edit the Manuscript by Language Editor	2022-05-19 11:12
Typeset the Manuscript	2022-06-27 08:59
Publish the Manuscript Online	2022-06-28 03:19

ISSN	2644-3228 (online)
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: http://creativecommons.org/licenses/by-nc/4.0/
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Category	Oncology
Manuscript Type	Minireviews
Article Title	Building and evaluating an artificial intelligence algorithm: A practical guide for practicing oncologists
Manuscript Source	Unsolicited Manuscript
All Author List	Anupama Ramachandran, Deeksha Bhalla, Krithika Rangarajan, Raja Pramanik, Subhashis Banerjee and Chetan Arora
ORCID	Author(s) ORCID Number Anupama Ramachandran http://orcid.org/0000-0002-5808-6076 Deeksha Bhalla http://orcid.org/0000-0003-0478-6859 Krithika Rangarajan http://orcid.org/0000-0001-5376-6390
Funding Agency and Grant Number
Corresponding Author	Krithika Rangarajan, MBBS, MD, Assistant Professor, Department of Radiology, All India Institute of Medical Sciences New Delhi, AIIMS, Ansari Nagar , New Delhi 110029, India. krithikarangarajan86@gmail.com
Key Words	Artificial intelligence; Precision medicine; Radiomics; Deep learning
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.
Publish Date	2022-06-28 03:19
Citation	Ramachandran A, Bhalla D, Rangarajan K, Pramanik R, Banerjee S, Arora C. Building and evaluating an artificial intelligence algorithm: A practical guide for practicing oncologists. Artif Intell Cancer 2022; 3(3): 42-53
URL	https://www.wjgnet.com/2644-3228/full/v3/i3/42.htm
DOI	https://dx.doi.org/10.35713/aic.v3.i3.42

Full Article (PDF)	AIC-3-42.pdf
Full Article (Word)	AIC-3-42.docx
Manuscript File	75772_Auto_Edited-LJH_WangTQ-LS.docx
Answering Reviewers	75772-Answering reviewers.pdf
Audio Core Tip	75772-Audio core tip.aac
Conflict-of-Interest Disclosure Form	75772-Conflict-of-interest statement.pdf
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Non-Native Speakers of English Editing Certificate	75772-Language certificate.pdf
Peer-review Report	75772-Peer-review(s).pdf
Scientific Misconduct Check	75772-Bing-Liu JH-2.jpg
Scientific Misconduct Check	75772-CrossCheck.jpg
Scientific Editor Work List	75772-Scientific editor work list.pdf
CrossCheck Report	75772-CrossCheck report.pdf