AIMC Topic: Ovarian Neoplasms

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Machine learning-derived diagnostic model of epithelial ovarian cancer based on gut microbiome signatures.

Journal of translational medicine
BACKGROUND: Prior studies have elucidated that alterations in gut microbiota are associated with a spectrum of tumors and metabolic disorders. However, the diagnostic value of gut microbiota in epithelial ovarian cancer remains insufficiently investi...

Nano biosensor unlocks tumor derived immune signals for the early detection of ovarian cancer.

Biosensors & bioelectronics
Ovarian cancer is a critical health issue for women nowadays. Its impact is significant because of its high mortality rate (324,603 worldwide), late-stage diagnosis and poor survival rate. Lack of screening tests, vague symptoms, misdiagnosis, and ag...

Multi-Omics Deep-Learning Prediction of Homologous Recombination Deficiency-Like Phenotype Improved Risk Stratification and Guided Therapeutic Decisions in Gynecological Cancers.

IEEE journal of biomedical and health informatics
Homologous recombination deficiency (HRD) is a well-recognized important biomarker in determining the clinical benefits of platinum-based chemotherapy and PARP inhibitor therapy for patients diagnosed with gynecologic cancers. Accurate prediction of ...

Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images.

Journal of translational medicine
BACKGROUND: Homologous recombination deficiency (HRD) refers to the dysfunction of homologous recombination repair (HRR) at the cellular level. The assessment of HRD status has the important significance for the formulation of treatment plans, effica...

Enhancing Personalized Chemotherapy for Ovarian Cancer: Integrating Gene Expression Data with Machine Learning.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE:  Ovarian cancer's complexity and heterogeneity pose significant challenges in treatment, often resulting in suboptimal chemotherapy outcomes. This study aimed to leverage machine learning algorithms, gene selection, and gene expression dat...

Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks.

Communications biology
Single-cell image analysis is crucial for studying drug effects on cellular morphology and phenotypic changes. Most studies focus on single cell types, overlooking the complexity of cellular interactions. Here, we establish an analysis pipeline to ex...

Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer.

Frontiers in immunology
BACKGROUND: Ovarian cancer (OC) is a severe malignant tumor with a significant threat to women's health, characterized by a high mortality rate and poor prognosis despite conventional treatments such as cytoreductive surgery and platinum-based chemot...

Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

Journal of cancer research and clinical oncology
PURPOSE: The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients...

A predictive model for recurrence in patients with borderline ovarian tumor based on neural multi-task logistic regression.

BMC cancer
BACKGROUND: Effective management of patients with borderline ovarian tumor (BOT) requires the timely identification of those at a higher risk of recurrence. Artificial neural networks have been successfully used in many areas of clinical event predic...

A metabolic fingerprint of ovarian cancer: a novel diagnostic strategy employing plasma EV-based metabolomics and machine learning algorithms.

Journal of ovarian research
Ovarian cancer (OC) is the third most common malignant tumor of women and is accompanied by an alteration of systemic metabolism. A liquid biopsy that captures and detects tumor-related biomarkers in body fluids has great potential for OC diagnosis. ...