alexa Fingerprints, Facial Recognition and Cancer
ISSN: 2169-0138

Drug Designing: Open Access
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Review Article

Fingerprints, Facial Recognition and Cancer

Roy J Vaz*

Division of Graduate Professional Studies, Rabb School of Continuing Studies, Brandeis University, Waltham, MA 02453, USA

Corresponding Author:
Roy J Vaz
Division of Graduate Professional Studies, Rabb School of Continuing Studies
Brandeis University, Waltham, MA 02453, United States
Tel: 781 434 3413
E-mail: [email protected]

Received Date: May 12, 2016; Accepted Date: June 21, 2016; Published Date: June 30, 2016

Citation: Vaz RJ (2016) Fingerprints, Facial Recognition and Cancer. Drug Des 5:133. doi:10.4172/2169-0138.1000133

Copyright: © 2016 Vaz RJ. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Images are unstructured data and are large in computer data storage size. Standard processes for Fingerprint Analysis, Facial Recognition and Treatment of Histopathological images for Diagnosis and Prognosis are utilized to show that an image can be processed to deliver structured data. This structured data is usually subjected to Machine Learning or Artificial Intelligence Analysis run on the associated server. The images themselves could be stored at locations where accession need not be as fast. The latest Artificial Intelligence tool (Deep Learning) is quite impressive and has been used in quite a few applications. The promise of its use with histopathological images could revolutionize the field of Breast Cancer prognosis and perhaps, even better treatments.

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