AIMC Topic: Carcinoma, Ovarian Epithelial

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Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

Annals of surgical oncology Mar 10, 2015
BACKGROUND: 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, convent...
Algorithms Prognosis Female Survival Rate Cytoreduction Surgical Procedures Humans Proportional Hazards Models Neural Networks, Computer Neoplasms, Glandular and Epithelial ROC Curve Support Vector Machine Decision Trees Ovarian Neoplasms Predictive Value of Tests Area Under Curve Bayes Theorem Carcinoma, Ovarian Epithelial
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Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer.

Biomedical engineering online May 13, 2025
BACKGROUND: The study aimed at developing and validating a deep learning (DL) model based on the ultrasound imaging for predicting the platinum resistance of patients with epithelial ovarian cancer (EOC).
Female Aged Adult Middle Aged Humans Deep Learning Ovarian Neoplasms Retrospective Studies Platinum Ultrasonography Carcinoma, Ovarian Epithelial ROC Curve Drug Resistance, Neoplasm Image Processing, Computer-Assisted
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Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records.

JCO clinical cancer informatics Jul 1, 2024
PURPOSE: Patients with epithelial ovarian cancer (EOC) have an elevated risk for venous thromboembolism (VTE). To assess the risk of VTE, models were developed by statistical or machine learning algorithms. However, few models have accommodated deep ...
Carcinoma, Ovarian Epithelial Venous Thromboembolism Risk Factors Prognosis Aged Electronic Health Records Adult Republic of Korea Risk Assessment Middle Aged Female Humans Deep Learning Neural Networks, Computer ROC Curve Algorithms Ovarian Neoplasms
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Platelet RNA signature independently predicts ovarian cancer prognosis by deep learning neural network model.

Protein & cell Aug 1, 2023
Female Deep Learning Ovarian Neoplasms RNA Humans Neural Networks, Computer Carcinoma, Ovarian Epithelial
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The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review.

Cancer control : journal of the Moffitt Cancer Center Jan 1, 2023
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.
Artificial Intelligence Female Ovarian Neoplasms Neoplasm Recurrence, Local Humans Carcinoma, Ovarian Epithelial Cytoreduction Surgical Procedures
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Robot-assisted laparoscopic staging compared to conventional laparoscopic staging and laparotomic staging in clinical early stage ovarian carcinoma.

Current opinion in oncology Sep 1, 2022
PURPOSE OF REVIEW: Robot-assisted laparoscopic staging (RALS) is increasingly used for staging epithelial ovarian cancer (EOC). Evidence of its safety is limited. The aim of this review is to compare the efficacy and safety of RALS in clinical early-...
Carcinoma Carcinoma, Ovarian Epithelial Laparotomy Humans Retrospective Studies Female Treatment Outcome Ovarian Neoplasms Robotics Neoplasm Staging Laparoscopy
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A chemotherapy response classifier based on support vector machines for high-grade serous ovarian carcinoma.

Oncotarget Jan 19, 2016
Long-term outcome of high-grade serous epithelial ovarian carcinoma (HGSOC) remains poor as a result of recurrence and the emergence of drug resistance. Almost all the patients were given the same platinum-based chemotherapy after debulking surgery e...
Cohort Studies Support Vector Machine Ovarian Neoplasms Neoplasm Recurrence, Local Disease-Free Survival Carcinoma, Ovarian Epithelial Drug Resistance, Neoplasm Neoplasms, Glandular and Epithelial Decision Support Techniques Female Middle Aged Antineoplastic Agents Humans Response Evaluation Criteria in Solid Tumors
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Assessing the association between 25-OH vitamin D levels and ROMA score in a population of obese women.

Journal of biological regulators and homeostatic agents Jan 1, 2016
The “Risk of Malignancy Algorithm” (ROMA) combines the diagnostic power of the CA125 and HE4 markers with menopausal status to predict the risk for developing epithelial ovarian cancer (EOC). The aim of this study was to evaluate the association betw...
Sensitivity and Specificity Carcinoma, Ovarian Epithelial Female Biomarkers, Tumor Enzyme-Linked Immunosorbent Assay Humans Neoplasms, Glandular and Epithelial Risk Factors Middle Aged Vitamin D Algorithms Young Adult ROC Curve Obesity Bone Density Adult Ovarian Neoplasms
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Intraoperative Diagnosis Support Tool for Serous Ovarian Tumors Based on Microarray Data Using Multicategory Machine Learning.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society Jan 1, 2016
OBJECTIVES: Serous borderline ovarian tumors (SBOTs) are a subtype of serous ovarian carcinoma with atypical proliferation. Frozen-section diagnosis has been used as an intraoperative diagnosis tool in supporting the fertility-sparing surgery by diag...
Carcinoma, Ovarian Epithelial Immunoenzyme Techniques Neoplasms, Glandular and Epithelial Monitoring, Intraoperative Cystadenocarcinoma, Serous Real-Time Polymerase Chain Reaction Predictive Value of Tests Reverse Transcriptase Polymerase Chain Reaction Female Blotting, Western RNA, Messenger Humans Gene Expression Regulation, Neoplastic Neoplasm Staging Survival Rate Machine Learning Support Vector Machine Biomarkers, Tumor Prognosis Databases, Genetic Gene Expression Profiling Ovarian Neoplasms
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