AIMC Topic: Ovarian Neoplasms
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A novel algorithm to improve specificity in ovarian cancer detection.
Cancer treatment and research communications
Nov 10, 2017
BACKGROUND: Measurement of autoantibodies (AAbs) to tumor associated antigens has been proposed to aid in the early detection of ovarian cancer with high specificity. Here we describe a multiplex approach to evaluate selected peptide epitopes of p53 ...
Integration of data mining classification techniques and ensemble learning to identify risk factors and diagnose ovarian cancer recurrence.
Artificial intelligence in medicine
Jun 10, 2017
Ovarian cancer is the second leading cause of deaths among gynecologic cancers in the world. Approximately 90% of women with ovarian cancer reported having symptoms long before a diagnosis was made. Literature shows that recurrence should be predicte...
A structured latent model for ovarian carcinoma subtyping from histopathology slides.
Medical image analysis
May 9, 2017
Accurate subtyping of ovarian carcinomas is an increasingly critical and often challenging diagnostic process. This work focuses on the development of an automatic classification model for ovarian carcinoma subtyping. Specifically, we present a novel...
Regarding "Robotic Versus Laparoscopic Staging for Early Ovarian Cancer: A Case-matched Control Study".
Journal of minimally invasive gynecology
May 5, 2017
Node-based differential network analysis in genomics.
Computational biology and chemistry
Apr 4, 2017
Gene dependency networks often undergo changes in response to different conditions. Understanding how these networks change across two conditions is an important task in genomics research. Most previous differential network analysis approaches assume...
A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.
Computational and mathematical methods in medicine
Aug 23, 2016
Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. There...
Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.
PloS one
Jul 15, 2016
Medical diagnostics is often a multi-attribute problem, necessitating sophisticated tools for analyzing high-dimensional biomedical data. Mining this data often results in two crucial bottlenecks: 1) high dimensionality of features used to represent ...
Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach.
Ultrasound in medicine & biology
Dec 20, 2015
The discrimination between benign and malignant adnexal masses in ultrasound images represents one of the most challenging problems in gynecologic practice. In the study described here, a new method for automatic discrimination of adnexal masses base...
Management of ovarian cancer in 14th gestational week of pregnancy by robotic approach with preservation of the fetus.
Gynecologic and obstetric investigation
Apr 8, 2015
The objective of this study is to present a rare case of pregnancy complicated with ovarian cancer managed by robotic surgery. A 36-year-old woman suffered from sudden onset of lower abdominal pain during her pregnancy at 14 weeks of gestation. As ma...
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...
Cytoreduction Surgical Procedures
Proportional Hazards Models
Neoplasms, Glandular and Epithelial
Prognosis
Female
Predictive Value of Tests
Survival Rate
Support Vector Machine
Area Under Curve
Humans
ROC Curve
Decision Trees
Bayes Theorem
Neural Networks, Computer
Ovarian Neoplasms
Carcinoma, Ovarian Epithelial
Algorithms
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