AIMC Topic: Ovarian Neoplasms
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An optimized siamese neural network with deep linear graph attention model for gynaecological abdominal pelvic masses classification.
Abdominal radiology (New York)
Oct 24, 2024
An adnexal mass, also known as a pelvic mass, is a growth that develops in or near the uterus, ovaries, fallopian tubes, and supporting tissues. For women suspected of having ovarian cancer, timely and accurate detection of a malignant pelvic mass is...
Intratumoral and Peritumoral Radiomics for Predicting the Prognosis of High-grade Serous Ovarian Cancer Patients Receiving Platinum-Based Chemotherapy.
Academic radiology
Sep 16, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL) prognostic model to evaluate the significance of intra- and peritumoral radiomics in predicting outcomes for high-grade serous ovarian cancer (HGSOC) patients receiving platin...
TriFusion enables accurate prediction of miRNA-disease association by a tri-channel fusion neural network.
Communications biology
Aug 30, 2024
The identification of miRNA-disease associations is crucial for early disease prevention and treatment. However, it is still a computational challenge to accurately predict such associations due to improper information encoding. Previous methods char...
Machine learning analysis of oxidative stress-related phenotypes for specific gene screening in ovarian cancer.
Environmental toxicology
Aug 20, 2024
BACKGROUND: Oxidative stress serves a crucial role in tumor development. However, the relationship between ovarian cancer and oxidative stress remains unknown. We aimed to create an oxidative stress-related prognostic signature to enhance the prognos...
Indirect reference interval estimation using a convolutional neural network with application to cancer antigen 125.
Scientific reports
Aug 20, 2024
Indirect methods for reference interval (RI) estimation, which use data acquired from routine pathology testing, have the potential to accelerate the establishment of RIs to account for variables such as gender and age to improve clinical assessments...
Accurate Identification of Cancer Cells in Complex Pre-Clinical Models Using a Deep-Learning Neural Network: A Transfection-Free Approach.
Advanced biology
Aug 12, 2024
3D co-cultures are key tools for in vitro biomedical research as they recapitulate more closely the in vivo environment while allowing a tighter control on the culture's composition and experimental conditions. The limited technologies available for ...
Single-detector multiplex imaging flow cytometry for cancer cell classification with deep learning.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Aug 5, 2024
Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged as a powerful tool for cell analysis in various biomedical fields such as cancer detection. In this study, we develop multiplex imaging flow cytometry...
Personalized approach to malignant struma ovarii: Insights from a web-based machine learning tool.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Aug 4, 2024
OBJECTIVES: Malignant struma ovarii (MSO) is a rare ovarian tumor characterized by mature thyroid tissue. The diverse symptoms and uncommon nature of MSO can create difficulties in its diagnosis and treatment. This study aimed to analyze data and use...
Deep Learning Artificial Intelligence Predicts Homologous Recombination Deficiency and Platinum Response From Histologic Slides.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Jul 31, 2024
PURPOSE: Cancers with homologous recombination deficiency (HRD) can benefit from platinum salts and poly(ADP-ribose) polymerase inhibitors. Standard diagnostic tests for detecting HRD require molecular profiling, which is not universally available.
Deep fine-KNN classification of ovarian cancer subtypes using efficientNet-B0 extracted features: a comprehensive analysis.
Journal of cancer research and clinical oncology
Jul 25, 2024
This study presents a robust approach for the classification of ovarian cancer subtypes through the integration of deep learning and k-nearest neighbor (KNN) methods. The proposed model leverages the powerful feature extraction capabilities of Effici...
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