AIMC Topic: Receptors, Estrogen
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Relevance of Machine Learning to Predict the Inhibitory Activity of Small Thiazole Chemicals on Estrogen Receptor.
Current computer-aided drug design
Jan 1, 2023
BACKGROUND: Drug discovery requires the use of hybrid technologies for the discovery of new chemical substances. One of those interesting strategies is QSAR via applying an artificial intelligence system that effectively predicts how chemical alterat...
Training, Validation, and Test of Deep Learning Models for Classification of Receptor Expressions in Breast Cancers From Mammograms.
JCO precision oncology
Nov 1, 2021
PURPOSE: The molecular subtype of breast cancer is an important component of establishing the appropriate treatment strategy. In clinical practice, molecular subtypes are determined by receptor expressions. In this study, we developed a model using d...
Calcific aortic valve disease: turning therapeutic discovery up a notch.
Nature reviews. Cardiology
May 1, 2021
Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer.
Briefings in bioinformatics
Mar 22, 2019
Breast cancer prognosis and administration of therapies are aided by knowledge of hormonal and HER2 receptor status. Breast cancer lacking estrogen receptors, progesterone receptors and HER2 receptors are difficult to treat. Regarding large data repo...
Cell Classification in ER-Stained Whole Slide Breast Cancer Images Using Convolutional Neural Network.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Hormone receptor status in breast carcinoma is determined primarily to identify patients who may benefit from hormonal therapy. Estrogen receptor (ER) is one of the hormone receptor positive factors which have been recognized as a marker for which wo...
A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.
Indian journal of pharmacology
Jan 1, 2018
CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details c...
Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution.
Clinical and translational science
Jan 1, 2018
Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are commonly utilized to gather additional clinical data elements needed for translational research. Howev...
The relationship between breast cancer treatment, tumour type and vitamin D level in pre- and postmenopausal women.
Neuro endocrinology letters
Dec 1, 2017
OBJECTIVE: Vitamin D deficiency has been linked to a higher risk of cancer. There is insufficient data regarding the influence of treatment on vitamin D status. The aim of this study was to compare pre- and post-treatment levels of 25(OH)D in premeno...
Developing a Manually Annotated Corpus of Clinical Letters for Breast Cancer Patients on Routine Follow-Up.
Studies in health technology and informatics
Jan 1, 2017
This paper introduces the annotation schema and annotation process for a corpus of clinical letters describing the disease course and treatment of oestrogen receptor positive breast cancer patients, after completion of primary surgery and radiotherap...
Management of bone loss in postmenopausal breast cancer patients treated with aromatase inhibitors.
Acta reumatologica portuguesa
Jan 1, 2015
Breast cancer is the most commonly diagnosed cancer among women, but despite survival rates improvement, it is still the second major cause of cancer related death. In postmenopausal women with estrogen receptor (ER) dependent breast cancer, hormone ...
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