Work

Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes

Year: 2017

Type: article

Source: ACS Nano

DOI: 10.1021/acsnano.7b05503

Authors: Jina Ko, Neha Bhagwat, Stephanie S. Yee, Natalia Ortiz, Amine Sahmoud, Taylor Black, Nicole M. Aiello, Lydie McKenzie, Mark O’Hara, Colleen Redlinger, Janae Romeo, Erica L. Carpenter, Ben Z. Stanger, David Issadore

Institution: University of Pennsylvania

Language: English

Topic: Extracellular vesicles in disease

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: American Cancer Society, Pancreatic Cancer Action Network, Pennsylvania Department of Health, Hartwell Foundation, National Cancer Institute, National Institute of Diabetes and Digestive and Kidney Diseases

Awards: G102342434, A cell-based liquid biopsy approach for early pancreatic cancer detection, A micro Hall chip for circulating microvesicle based cancer monitoring, G499207949, Real-time monitoring of circulating pancreatic tumor cells and clusters, Immunobiology and immunotherapy of pancreatic cancer, G8700962575

OpenAlex ID: W2762354841

FWCI: 7.477

Cites: 63

Cited by: 248

Related to: 10