Publication Name	World Journal of Clinical Oncology
Manuscript ID	94813
Country	China

Received	2024-03-26 04:51
Peer-Review Started	2024-03-26 04:51
To Make the First Decision
Return for Revision	2024-05-09 07:23
Revised	2024-05-17 14:27
Second Decision	2024-06-05 02:43
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-06-05 07:44
Articles in Press	2024-06-05 07:44
Publication Fee Transferred
Edit the Manuscript by Language Editor	2024-10-21 21:52
Typeset the Manuscript	2024-10-29 02:37
Publish the Manuscript Online	2024-10-30 10:05

ISSN	2218-4333 (online)
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Category	Medical Informatics
Manuscript Type	Clinical and Translational Research
Article Title	Unlocking the future: Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response
Manuscript Source	Unsolicited Manuscript
All Author List	Zhi-Jian Tang, Yuan-Ming Pan, Wei Li, Rui-Qiong Ma and Jian-Liu Wang
ORCID	Author(s) ORCID Number Wei Li http://orcid.org/0000-0003-0471-2382 Jian-Liu Wang http://orcid.org/0000-0003-0338-0427
Funding Agency and Grant Number	Funding Agency Grant Number National Key Technology Research and Developmental Program of China 2022YFC2704400 and 2022YFC2704405
Corresponding Author	Jian-Liu Wang, MD, Professor, Department of Obstetrics and Gynecology, Peking University People’s Hospital, No. 11 Xizhimen South Street, Beijing 100044, China. wangjianliu@pkuph.edu.cn
Key Words	Ovarian cancer; Mitochondria; Prognosis; Immunotherapy; Neural network
Core Tip	In this study, we found that mitochondrial genes and neural networks can be used to predict ovarian cancer prognosis and immunotherapy response. These models were evaluated in detail. The average area under the receiver operating characteristic curve (AUC) of the prognostic model was 0.7268 and 0.6475 for the discovery and validation cohorts, respectively. The average AUC of the immunotherapy efficacy model was 0.9444 and 0.9167 for the discovery and validation cohorts, respectively. The Hosmer-Lemeshow goodness of fit test showed that the model had a good calibration performance. Therefore, we compressed above neural network as a clinical tool.
Publish Date	2024-10-30 10:05
Citation	<p>Tang ZJ, Pan YM, Li W, Ma RQ, Wang JL. Unlocking the future: Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response. <i>World J Clin Oncol</i> 2025; 16(1): 94813</p>
URL	https://www.wjgnet.com/2218-4333/full/v16/i1/94813.htm
DOI	https://dx.doi.org/10.5306/wjco.v16.i1.94813

Full Article (PDF)	WJCO-16-94813-with-cover.pdf
Manuscript File	94813_Auto_Edited_010840.docx
Answering Reviewers	94813-answering-reviewers.pdf
Audio Core Tip	94813-audio.mp3
Biostatistics Review Certificate	94813-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	94813-conflict-of-interest-statement.pdf
Copyright License Agreement	94813-copyright-assignment.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	94813-foundation-statement.pdf
Non-Native Speakers of English Editing Certificate	94813-non-native-speakers.pdf
Supplementary Material	94813-supplementary-material.pdf
Peer-review Report	94813-peer-reviews.pdf
Scientific Misconduct Check	94813-scientific-misconduct-check.jpg
Scientific Editor Work List	94813-scientific-editor-work-list.pdf
CrossCheck Report	94813-crosscheck-report.pdf