AIMC Topic: DNA Mutational Analysis

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Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images.

The journal of pathology. Clinical research
EGFR mutations are a major prognostic factor in lung adenocarcinoma. However, current detection methods require sufficient samples and are costly. Deep learning is promising for mutation prediction in histopathological image analysis but has limitati...

Validity of Natural Language Processing for Ascertainment of and Test Results in SEER Cases of Stage IV Non-Small-Cell Lung Cancer.

JCO clinical cancer informatics
PURPOSE: SEER registries do not report results of epidermal growth factor receptor () and anaplastic lymphoma kinase () mutation tests. To facilitate population-based research in molecularly defined subgroups of non-small-cell lung cancer (NSCLC), we...

Machine learning from concept to clinic: reliable detection of BRAF V600E DNA mutations in thyroid nodules using high-dimensional RNA expression data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The promise of personalized medicine will require rigorously validated molecular diagnostics developed on minimally invasive, clinically relevant samples. Measurement of DNA mutations is increasingly common in clinical settings but only higher-preval...