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Ovarian Neoplasms

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Stratification of Length of Stay Prediction following Surgical Cytoreduction in Advanced High-Grade Serous Ovarian Cancer Patients Using Artificial Intelligence; the Leeds L-AI-OS Score.

Current oncology (Toronto, Ont.)
(1) Background: Length of stay (LOS) has been suggested as a marker of the effectiveness of short-term care. Artificial Intelligence (AI) technologies could help monitor hospital stays. We developed an AI-based novel predictive LOS score for advanced...

Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging.

BMC medical informatics and decision making
BACKGROUND: Upon the discovery of ovarian cysts, obstetricians, gynecologists, and ultrasound examiners must address the common clinical challenge of distinguishing between benign and malignant ovarian tumors. Numerous types of ovarian tumors exist, ...

DeepCAN: A Modular Deep Learning System for Automated Cell Counting and Viability Analysis.

IEEE journal of biomedical and health informatics
Precise and quick monitoring of key cytometric features such as cell count, size, morphology, and DNA content is crucial in life science applications. Traditionally, image cytometry relies on visual inspection of hemocytometers. This approach is erro...

Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder.

Scientific reports
Discrimination of ovarian tumors is necessary for proper treatment. In this study, we developed a convolutional neural network model with a convolutional autoencoder (CNN-CAE) to classify ovarian tumors. A total of 1613 ultrasound images of ovaries w...

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

BioMed research international
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...

Automatic Detection and Segmentation of Ovarian Cancer Using a Multitask Model in Pelvic CT Images.

Oxidative medicine and cellular longevity
Ovarian cancer is one of the most common malignant tumours of female reproductive organs in the world. The pelvic CT scan is a common examination method used for the screening of ovarian cancer, which shows the advantages in safety, efficiency, and p...

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

International journal of molecular sciences
BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessment is not sufficient to identify all patients with genomic instability, since BRCA 1/2 mutations ar...

Deep learning-based histotype diagnosis of ovarian carcinoma whole-slide pathology images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Ovarian carcinoma has the highest mortality of all female reproductive cancers and current treatment has become histotype-specific. Pathologists diagnose five common histotypes by microscopic examination, however, histotype determination is not strai...

Ovarian Cancer-Self Assessment: An Innovation for Early Detection and Risk Assessment of Ovarian Cancer.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: The modality to detect ovarian cancer at an early stage is very limited. Early diagnosis determines the prognosis. This study aimed to develop a risk assessment tool for early detection of ovarian cancer using artificial intelligence. To a...

Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian cancer, more than 70 % of advanced patients are with recurrent cancer and decease. Surgical debulking of tumors following chemotherapy is the conventiona...