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Volume 8
Journal of Clinical & Experimental Pathology
Page 13
Notes:
conference
series
.com
September 17-18, 2018 Tokyo Japan
Joint Event on
33
rd
International Conference on
and
Oncology Nursing and Cancer Care
16
th
Asia Pacific Pathology Congress
Cancer Nursing & Pathology Congress 2018
September 17-18, 2018
Using an artificial intelligence pipeline for digital pathology
T
he utility of an artificial intelligence (AI) pipeline for digital pathology is advancing rapidly as computational capabilities
and information technology improve. The AI pipeline involves complicated algorithm design along with harmonized pre-
analytical image processing to achieve satisfactory sensitivity and specificity. An AI pipeline has been adopted as a tool to
assist in screening cytopathology, differential diagnosis and scoring of solid tumors, variant annotation in genomic studies,
and karyotyping in cytogenomics. Challenges include the regulatory environment for screening and diagnosis, standardization
of platforms and imaging sharing, harmonization of imaging quality and requirements, continual algorithm improvements
and revisions, an extensive amount of data analysis and storage, and training and education of digital image readers and
technologies.
Biography
Jia-Chi Wang completed his M.D. in Taiwan and his
M.Sc. and Ph.D. at McGill University in Canada. He is an associate professor of National Cheng-Kung
University (Taiwan) and senior director of cytogenomics and molecular genetics laboratories at Quest Diagnostics. He has published over 40 peer-reviewed papers
and serves on an editorial board and reviewer for peer-reviewed journals.
Jia-Chi.J.Wang@questdiagnostics.comJia-Chi Wang
Quest Diagnostics, USA
Jia-Chi Wang, J Clin Exp Pathol 2018, Volume 8
DOI: 10.4172/2161-0681-C4-053