AIMC Topic: Receptor, ErbB-2

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Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

Nature biomedical engineering
The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because of the low-throughput screening of full-length antibodies (approximately 1 × 10 variants) expressed in mammalian cells, which typically results in fe...

MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer.

EBioMedicine
BACKGROUND: To use clinical and MRI radiomic features coupled with machine learning to assess HER2 expression level and predict pathologic response (pCR) in HER2 overexpressing breast cancer patients receiving neoadjuvant chemotherapy (NAC).

Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E images.

Scientific reports
Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorith...

A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival.

Breast cancer research : BCR
BACKGROUND: Breast cancer intrinsic molecular subtype (IMS) as classified by the expression-based PAM50 assay is considered a strong prognostic feature, even when controlled for by standard clinicopathological features such as age, grade, and nodal s...

Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer.

JAMA network open
IMPORTANCE: Immunohistochemistry (IHC) is the most widely used assay for identification of molecular biomarkers. However, IHC is time consuming and costly, depends on tissue-handling protocols, and relies on pathologists' subjective interpretation. I...

Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records.

Scientific reports
Electronic health records (EHR) represent a rich resource for conducting observational studies, supporting clinical trials, and more. However, much of the data contains unstructured text, presenting an obstacle to automated extraction. Natural langua...

An Intelligent DNA Nanorobot with Enhanced Protein Lysosomal Degradation of HER2.

Nano letters
DNA nanorobots have emerged as new tools for nanomedicine with the potential to ameliorate the delivery and anticancer efficacy of various drugs. DNA nanostructures have been considered one of the most promising nanocarriers. In the present study, we...

Automated segmentation of cell membranes to evaluate HER2 status in whole slide images using a modified deep learning network.

Computers in biology and medicine
The uncontrollable growth of cells in the breast tissue causes breast cancer which is the second most common type of cancer affecting women in the United States. Normally, human epidermal growth factor receptor 2 (HER2) proteins are responsible for t...