AIMC Topic: Ovarian Neoplasms
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Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging.
European radiology
Oct 14, 2020
OBJECTIVES: There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study developed a deep learning algorithm that distinguishes benign from malignant ovarian lesion by apply...
Natural language processing with machine learning to predict outcomes after ovarian cancer surgery.
Gynecologic oncology
Oct 14, 2020
OBJECTIVE: To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improves the ability to predict postoperative complication and hospital readmission among women with ovari...
Predicting complete cytoreduction for advanced ovarian cancer patients using nearest-neighbor models.
Journal of ovarian research
Sep 29, 2020
BACKGROUND: The foundation of modern ovarian cancer care is cytoreductive surgery to remove all macroscopic disease (R0). Identification of R0 resection patients may help individualise treatment. Machine learning and AI have been shown to be effectiv...
Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.
Scientific reports
Sep 10, 2020
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...
Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.
Methods (San Diego, Calif.)
Aug 5, 2020
Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-...
Common cancer biomarkers of breast and ovarian types identified through artificial intelligence.
Chemical biology & drug design
May 15, 2020
Biomarkers can offer great promise for improving prevention and treatment of complex diseases such as cancer, cardiovascular diseases, and diabetes. These can be used as either diagnostic or predictive or as prognostic biomarkers. The revolution brou...
EnvCNN: A Convolutional Neural Network Model for Evaluating Isotopic Envelopes in Top-Down Mass-Spectral Deconvolution.
Analytical chemistry
May 13, 2020
Top-down mass spectrometry has become the main method for intact proteoform identification, characterization, and quantitation. Because of the complexity of top-down mass spectrometry data, spectral deconvolution is an indispensable step in spectral ...
Prediction of Postoperative Length of Hospital Stay Based on Differences in Nursing Narratives in Elderly Patients with Epithelial Ovarian Cancer.
Methods of information in medicine
Apr 29, 2020
OBJECTIVES:  The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer.
Joint learning improves protein abundance prediction in cancers.
BMC biology
Dec 23, 2019
BACKGROUND: The classic central dogma in biology is the information flow from DNA to mRNA to protein, yet complicated regulatory mechanisms underlying protein translation often lead to weak correlations between mRNA and protein abundances. This is pa...
Machine learning and bioinformatics models to identify gene expression patterns of ovarian cancer associated with disease progression and mortality.
Journal of biomedical informatics
Oct 23, 2019
Ovarian cancer (OC) is a common cause of cancer death among women worldwide, so there is a pressing need to identify factors influencing OC mortality. Much OC patient clinical data is publicly accessible via the Broad Institute Cancer Genome Atlas (T...
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