Automated Molecular Subtyping of Breast Carcinoma using Deep Learning Techniques

Objective: Molecular subtyping is an important procedure for prognosis and targeted therapy of breast carcinoma, the most common type of malignancy affecting women. Immunohistochemistry (IHC) analysis is the widely accepted method for molecular subtyping. It involves the assessment of the four molec...

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Veröffentlicht in:	IEEE journal of translational engineering in health and medicine 2023-01, Vol.11, p.1-1
Hauptverfasser:	Niyas, S, Bygari, Ramya, Naik, Rachita, Viswanath, Bhavishya, Ugwekar, Dhananjay, Mathew, Tojo, Kavya, J, Kini, Jyoti R, Rajan, Jeny
Format:	Artikel
Sprache:	eng
Schlagworte:	Antibodies Antigens Artificial neural networks Automation Biological system modeling Biomarkers Breast Breast cancer Breast Neoplasms - metabolism Coders Deep Learning Estrogens Female Growth factors Humans Image segmentation Immune system Immunohistochemistry Ki-67 Antigen Medical treatment Molecular subtyping Reagents Receptors Receptors, Estrogen - metabolism
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