Efficient Spatial Sampling for AFM-Based Cancer Diagnostics: A Comparison between Neural Networks an...
Efficient Spatial Sampling for AFM-Based Cancer Diagnostics: A Comparison between Neural Networks and Conventional Data Analysis
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Basel: MDPI AG
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English
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Basel: MDPI AG
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Atomic force microscopy (AFM) in spectroscopy mode receives a lot of attention because of its potential in distinguishing between healthy and cancer tissues. However, the AFM translational process in clinical practice is hindered by the fact that it is a time-consuming technique in terms of measurement and analysis time. In this paper, we attempt t...
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Efficient Spatial Sampling for AFM-Based Cancer Diagnostics: A Comparison between Neural Networks and Conventional Data Analysis
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TN_cdi_doaj_primary_oai_doaj_org_article_01ece3b3b14c4da88d902b0ea470f292
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_01ece3b3b14c4da88d902b0ea470f292
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ISSN
2410-3896
E-ISSN
2410-3896
DOI
10.3390/condmat4020058
