Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer

Annals of Surgical Oncology
A EnshaeiR J Edmondson

Abstract

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict ...Continue Reading

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Citations

Oct 24, 2015·Nature Reviews. Cancer·David D BowtellFrances R Balkwill
May 16, 2020·Current Pharmaceutical Design·Abhimanyu ThakurBabita Majhi
Apr 14, 2019·Clinical Cancer Research : an Official Journal of the American Association for Cancer Research·Eiryo KawakamiAikou Okamoto
Dec 29, 2020·Cancer Management and Research·Jie ZhouLi Li
May 26, 2021·Obstetrical & Gynecological Survey·David Pierce MysonaJohn K Chan
Oct 26, 2021·Cancer Control : Journal of the Moffitt Cancer Center·Alexandros LaiosDiederick De Jong

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