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Ovarian Neoplasms

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Machine learning and biological evaluation-based identification of a potential MMP-9 inhibitor, effective against ovarian cancer cells SKOV3.

Journal of biomolecular structure & dynamics
MMP-9, also known as gelatinase B, is a zinc-metalloproteinase family protein that plays a key role in the degradation of the extracellular matrix (ECM). The normal function of MMP-9 includes the breakdown of ECM, a process that aids in normal physio...

Predicting Neoadjuvant Chemotherapy Response and High-Grade Serous Ovarian Cancer From CT Images in Ovarian Cancer with Multitask Deep Learning: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate prediction neoadjuvant chemotherapy (NACT) response in ovarian cancer (OC) is essential for personalized medicine. We aimed to develop and validate a deep learning (DL) model based on pretreatment contrast-enhanced ...

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer.

The Analyst
Mid-infrared spectroscopic imaging (MIRSI) is an emerging class of label-free techniques being leveraged for digital histopathology. Modern histopathologic identification of ovarian cancer involves tissue staining followed by morphological pattern re...

Associating Peritoneal Metastasis With T2-Weighted MRI Images in Epithelial Ovarian Cancer Using Deep Learning and Radiomics: A Multicenter Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The preoperative diagnosis of peritoneal metastasis (PM) in epithelial ovarian cancer (EOC) is challenging and can impact clinical decision-making.

A Deep Learning-Based System Trained for Gastrointestinal Stromal Tumor Screening Can Identify Multiple Types of Soft Tissue Tumors.

The American journal of pathology
The accuracy and timeliness of the pathologic diagnosis of soft tissue tumors (STTs) critically affect treatment decision and patient prognosis. Thus, it is crucial to make a preliminary judgement on whether the tumor is benign or malignant with hema...

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis.

Journal of biomedical informatics
OBJECTIVE: Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to identi...

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies widely tested in anti-cancer treatment, i.e. VEGF-targeting monoclonal antibody bevacizumab, in combination with chemotherapy for frontline and mainte...

Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging.

Scientific reports
To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT) from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively enrolled 201 patients of 102 pathologically proven BOTs and 99 EOCs at OB/GY...

Robotic omentectomy in gynecologic oncology: surgical anatomy, indications, and a technical approach.

Journal of robotic surgery
An omentectomy is a standard component care of gynecological cancers, particularly for surgical staging and treatment for malignant ovarian neoplasms, borderline tumors, fallopian tube cancers, primary peritoneal cancers as well as certain histologic...

Application of machine learning techniques for predicting survival in ovarian cancer.

BMC medical informatics and decision making
BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States. Ovarian cancer is also known as forgotten cancer or silent disease. The survival of ovarian cancer patients depends on several factors, including the...