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|author1=Al Young |author2=Dayle Woolstein |author3=Jay Johnson}}</ref>
 
A technology called automatic document processing or sometimes intelligent document processing is rapidly emerging,emerged as a specific form of [[Process Automation|Intelligent Process Automation]] (IPA), and combinescombining [[artificial intelligence]] such as [[Machine Learning]] (ML), [[Natural Language Processing]] (NLP) or [[Intelligent Character Recognition]] (ICR) to extract data from unstructuredseveral types documents such as paper-based invoices, forms, purchase orders, and contracts.<ref>{{Cite web|url=http://www.di.uniba.it/~ndm/pubs/esposito05icdar.pdf|title=Intelligent Document processing by Floriana Esposito , Stefano Ferilli , Teresa M. A. Basile , Nicola Di Mauro|date=2005-04-07|website=Department of Computer Science – University of Bari|access-date=2018-09-08}}</ref><ref>{{Cite book
|url=https://www.computer.org/csdl/proceedings-article/icdar/2005/24201100/12OmNqIQS59
|title="Intelligent Document Processing" in Proceedings. Eighth International Conference on Document Analysis and Recognition, Seoul, South Korea, 2005 pp. 1100-1104. doi: 10.1109/ICDAR.2005.144
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|publisher= |isbn=}}</ref>
 
==See= alsoApplication ===
Automatic document processing applies to a whole range of documents, whether structured or not. For instance, in the world of business and finance, technologies may be used to process paper-based invoices, forms, purchase orders, contracts, and currency bills<ref>{{cite patent |country=US|number=US7873576B2|status=active|title= Financial document processing system |pubdate=2011-01-18|gdate=2011-01-18|invent1=John E. Jones|invent2=William J. Jones|invent3=Frank M. Csultis|url=https://patents.google.com/patent/US7873576B2/en}}</ref>.
 
In medicine, document processing methods have been developed to facilitate patient follow-up and streamline administrative procedures, in particular by digitizing medical or laboratory analysis reports. The goal is also to standardize medical databases<ref>{{cite journal |last1=Adamo|first1=Francesco|last2=Attivissimo|first2=Filippo|first3=Attilio|last3=Di Nisio|first4=Maurizio|last4=Spadavecchia|date=February 2015|title=An automatic document processing system for medical data extraction|url=https://www.sciencedirect.com/science/article/pii/S0263224114005016?casa_token=heNt0-b7OZQAAAAA:uvH1ZRZOGIw3XbLF245ePomFOwVl8svsdARmurepRv7G7vcISA9Gc8d5ZhmcG6Y0RJTJeJ2Sn98|journal=Measurement|volume=61|pages=88-99 |doi=10.1016/j.measurement.2014.10.032|access-date=31 January 2021}}</ref>. Algorithms are also directly used to assist the physicians in medical diagnosis, e.g. by analyzing [[Magnetic resonance imaging|magnetic resonance images]]<ref>{{cite journal |last1=Changwan|first1=Kim|last2=Seong-Il|first2=Lee|last3=Won Joon|first3=Cho|date=September 2020|title=Volumetric assessment of extrusion in medial meniscus posterior root tears through semi-automatic segmentation on 3-tesla magnetic resonance images|url=https://www.sciencedirect.com/science/article/abs/pii/S1877051720301994|journal=Orthopaedics & Traumatology: Surgery & Research|volume=101|issue=5|pages=963-968|doi=10.1016/j.rcot.2020.06.003|access-date=31 January 2021}}</ref>.
 
== See also ==
* [[Document automation]]
* [[Document modelling]]
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