Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and...
Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features
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Publisher
Switzerland: MDPI AG
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Language
English
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Publisher
Switzerland: MDPI AG
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Contents
Despite advances in diagnostic techniques, accurate classification of lung cancer subtypes remains crucial for treatment planning. Traditional methods like genomic studies face limitations such as high cost and complexity. This study investigates whether integrating atomic force microscopy (AFM) measurements with conventional clinical and histopath...
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Full title
Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features
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TN_cdi_doaj_primary_oai_doaj_org_article_0d308d5d5faa4983834e653dccfb6580
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0d308d5d5faa4983834e653dccfb6580
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ISSN
2075-4418
E-ISSN
2075-4418
DOI
10.3390/diagnostics15020127
