Machine learning-based approach for automated classification of cell and extracellular matrix using nanomechanical properties

Tanmay Kulkarni; Olivia Marie Robinson; Ayan Dutta; Debabrata Mukhopadhyay; Santanu Bhattacharya

doi:10.1016/j.mtbio.2024.100970

Machine learning-based approach for automated classification of cell and extracellular matrix using nanomechanical properties

Tanmay Kulkarni
, Olivia Marie Robinson
, Ayan Dutta
, Debabrata Mukhopadhyay
, Santanu Bhattacharya

School of Computing

Producción científica: Article › revisión exhaustiva

Idioma original	English
Número de artículo	100970
Páginas (desde-hasta)	100970
Publicación	Materials Today Bio
Volumen	25
DOI	https://doi.org/10.1016/j.mtbio.2024.100970
Estado	Published - abr 2024

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Good health and well being

ASJC Scopus Subject Areas

Biotechnology
Bioengineering
Biomaterials
Biomedical Engineering
Molecular Biology
Cell Biology

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10.1016/j.mtbio.2024.100970

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title = "Machine learning-based approach for automated classification of cell and extracellular matrix using nanomechanical properties",

keywords = "Extracellular matrix, Fibrosis, Machine learning, Nanomechanical attributes, Pancreatic cancer, Support vector machines",

author = "Tanmay Kulkarni and Robinson, \{Olivia Marie\} and Ayan Dutta and Debabrata Mukhopadhyay and Santanu Bhattacharya",

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AU - Bhattacharya, Santanu

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KW - Nanomechanical attributes

KW - Pancreatic cancer

KW - Support vector machines

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M3 - Article

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JO - Materials Today Bio

JF - Materials Today Bio

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ER -

Machine learning-based approach for automated classification of cell and extracellular matrix using nanomechanical properties

ODS de las Naciones Unidas

ASJC Scopus Subject Areas

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