Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review
by
Zola, Paolo
, Piovano, Elisa
, Parpinel, Giulia
, Laudani, Maria Elena
, Lecuru, Fabrice
in
Accuracy
/ Algorithms
/ An Inventory of Epithelial Ovarian Cancer Targets: “Evidence-based” Options-Review
/ Artificial Intelligence
/ Carcinoma, Ovarian Epithelial - surgery
/ Clinical trials
/ Cytoreduction Surgical Procedures - methods
/ Female
/ Humans
/ Neoplasm Recurrence, Local - drug therapy
/ Ovarian cancer
/ Ovarian Neoplasms - surgery
/ Patients
/ Regression analysis
/ Surgery
/ Survival
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review
by
Zola, Paolo
, Piovano, Elisa
, Parpinel, Giulia
, Laudani, Maria Elena
, Lecuru, Fabrice
in
Accuracy
/ Algorithms
/ An Inventory of Epithelial Ovarian Cancer Targets: “Evidence-based” Options-Review
/ Artificial Intelligence
/ Carcinoma, Ovarian Epithelial - surgery
/ Clinical trials
/ Cytoreduction Surgical Procedures - methods
/ Female
/ Humans
/ Neoplasm Recurrence, Local - drug therapy
/ Ovarian cancer
/ Ovarian Neoplasms - surgery
/ Patients
/ Regression analysis
/ Surgery
/ Survival
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review
by
Zola, Paolo
, Piovano, Elisa
, Parpinel, Giulia
, Laudani, Maria Elena
, Lecuru, Fabrice
in
Accuracy
/ Algorithms
/ An Inventory of Epithelial Ovarian Cancer Targets: “Evidence-based” Options-Review
/ Artificial Intelligence
/ Carcinoma, Ovarian Epithelial - surgery
/ Clinical trials
/ Cytoreduction Surgical Procedures - methods
/ Female
/ Humans
/ Neoplasm Recurrence, Local - drug therapy
/ Ovarian cancer
/ Ovarian Neoplasms - surgery
/ Patients
/ Regression analysis
/ Surgery
/ Survival
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review
Journal Article
The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Introduction
In patients affected by epithelial ovarian cancer (EOC) complete cytoreduction (CC) has been associated with higher survival outcomes. Artificial intelligence (AI) systems have proved clinical benefice in different areas of healthcare.
Objective
To systematically assemble and analyze the available literature on the use of AI in patients affected by EOC to evaluate its applicability to predict CC compared to traditional statistics.
Material and Methods
Data search was carried out through PubMed, Scopus, Ovid MEDLINE, Cochrane Library, EMBASE, international congresses and clinical trials. The main search terms were: Artificial Intelligence AND surgery/cytoreduction AND ovarian cancer. Two authors independently performed the search by October 2022 and evaluated the eligibility criteria. Studies were included when data about Artificial Intelligence and methodological data were detailed.
Results
A total of 1899 cases were analyzed. Survival data were reported in 2 articles: 92% of 5-years overall survival (OS) and 73% of 2-years OS. The median area under the curve (AUC) resulted 0,62. The model accuracy for surgical resection reported in two articles reported was 77,7% and 65,8% respectively while the median AUC was 0,81. On average 8 variables were inserted in the algorithms. The most used parameters were age and Ca125.
Discussion
AI revealed greater accuracy compared against the logistic regression models data. Survival predictive accuracy and AUC were lower for advanced ovarian cancers. One study analyzed the importance of factors predicting CC in recurrent epithelial ovarian cancer and disease free interval, retroperitoneal recurrence, residual disease at primary surgery and stage represented the main influencing factors. Surgical Complexity Scores resulted to be more useful in the algorithms than pre-operating imaging.
Conclusion
AI showed better prognostic accuracy if compared to conventional algorithms. However further studies are needed to compare the impact of different AI methods and variables and to provide survival informations.
Publisher
SAGE Publications,Sage Publications Ltd,SAGE Publishing
This website uses cookies to ensure you get the best experience on our website.