AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cystadenocarcinoma, Serous

Showing 11 to 20 of 20 articles

Clear Filters

Comparison of lymphedema incidence between 2 lymphadenectomy techniques in patients with uterine cancer undergoing robotic staging.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society 25386859
OBJECTIVE: This study aimed to compare the incidence of lower extremity lymphedema in patients with uterine cancer after robotic staging using the following 2 methods: standard and selective pelvic lymphadenectomy.
Adenocarcinoma, Clear Cell Adult Aged Aged, 80 and over Carcinoma, Endometrioid Carcinosarcoma Connecticut Cystadenocarcinoma, Serous Endometrial Neoplasms Female Follow-Up Studies Humans Incidence Lymph Node Excision Lymph Nodes Lymphatic Metastasis Lymphedema Middle Aged Neoplasm Staging Para-Aortic Bodies Pelvic Neoplasms Prognosis Robotics Uterine Neoplasms
View on PubMed DOI

Intraoperative Diagnosis Support Tool for Serous Ovarian Tumors Based on Microarray Data Using Multicategory Machine Learning.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society 26512784
OBJECTIVES: Serous borderline ovarian tumors (SBOTs) are a subtype of serous ovarian carcinoma with atypical proliferation. Frozen-section diagnosis has been used as an intraoperative diagnosis tool in supporting the fertility-sparing surgery by diag...
Biomarkers, Tumor Blotting, Western Carcinoma, Ovarian Epithelial Cystadenocarcinoma, Serous Databases, Genetic Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Immunoenzyme Techniques Machine Learning Monitoring, Intraoperative Neoplasm Staging Neoplasms, Glandular and Epithelial Ovarian Neoplasms Predictive Value of Tests Prognosis Real-Time Polymerase Chain Reaction Reverse Transcriptase Polymerase Chain Reaction RNA, Messenger Support Vector Machine Survival Rate
View on PubMed DOI

High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.

Journal of the American College of Radiology : JACR 29789232
PURPOSE: The aim of this study was to use machine learning to predict abdominal recurrence on CT on the basis of serial cancer antigen 125 (CA125) levels in patients with advanced high-grade serous ovarian cancer on surveillance.
Biomarkers, Tumor CA-125 Antigen Cystadenocarcinoma, Serous Female Humans Machine Learning Middle Aged Neoplasm Recurrence, Local Neoplasm Staging Ovarian Neoplasms Predictive Value of Tests Retrospective Studies Risk Factors Tomography, X-Ray Computed
View on PubMed DOI

Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 30392780
BACKGROUND AND PURPOSE: Recurrence is the main risk for high-grade serous ovarian cancer (HGSOC) and few prognostic biomarkers were reported. In this study, we proposed a novel deep learning (DL) method to extract prognostic biomarkers from preoperat...
Biomarkers, Tumor Cohort Studies Cystadenocarcinoma, Serous Deep Learning Disease-Free Survival Female Humans Kaplan-Meier Estimate Middle Aged Neoplasm Recurrence, Local Ovarian Neoplasms Precision Medicine Predictive Value of Tests Prognosis Tomography, X-Ray Computed
View on PubMed DOI

Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers.

Gynecologic oncology 31796203
OBJECTIVE: Determine the utility of a clinical calculator to predict the benefit of chemotherapy in stage IA uterine papillary serous cancer (UPSC).
Aged Algorithms Cystadenocarcinoma, Papillary Cystadenocarcinoma, Serous Female Humans Machine Learning Neoplasm Staging Nomograms Predictive Value of Tests Prognosis Proportional Hazards Models Reproducibility of Results Uterine Neoplasms
View on PubMed DOI

Feature Selection is Critical for 2-Year Prognosis in Advanced Stage High Grade Serous Ovarian Cancer by Using Machine Learning.

Cancer control : journal of the Moffitt Cancer Center 34693730
INTRODUCTION: Accurate prediction of patient prognosis can be especially useful for the selection of best treatment protocols. Machine Learning can serve this purpose by making predictions based upon generalizable clinical patterns embedded within le...
Adult Age Factors Aged Aged, 80 and over Cystadenocarcinoma, Serous Female Humans Logistic Models Machine Learning Middle Aged Ovarian Neoplasms Patient Acuity Prognosis Prospective Studies Support Vector Machine
View on PubMed DOI

Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets.

Briefings in bioinformatics 32533167
The significance of pan-cancer categories has recently been recognized as widespread in cancer research. Pan-cancer categorizes a cancer based on its molecular pathology rather than an organ. The molecular similarities among multi-omics data found in...
Breast Neoplasms Computational Biology Cystadenocarcinoma, Serous Databases, Genetic Female Gene Regulatory Networks Genomics Humans Machine Learning Neoplasms Ovarian Neoplasms
View on PubMed DOI

Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.

Scientific reports 34580357
High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist ...
Adult Aged Artificial Intelligence Chemotherapy, Adjuvant Cystadenocarcinoma, Serous Fallopian Tube Neoplasms Female Humans Middle Aged Neural Networks, Computer Ovarian Neoplasms Peritoneal Neoplasms Platinum Compounds Retrospective Studies Treatment Outcome
View on PubMed DOI

Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers.

Scientific reports 35197484
Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cas...
Biomarkers, Tumor Correlation of Data Cystadenocarcinoma, Serous Databases, Factual Decision Trees Female Humans Machine Learning Ovarian Neoplasms Phenotype Prognosis Proteomics
View on PubMed DOI

A Deep Learning-Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma.

The American journal of pathology 38537936
Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study develo...
Aged Cystadenocarcinoma, Serous Deep Learning Female Humans Intraepithelial Lymphocytes Lymphocytes, Tumor-Infiltrating Middle Aged Ovarian Neoplasms Prognosis Stromal Cells
View on PubMed DOI
Popular Topics
Recent Journals