Using Semi-Automated Annotation and Optical Character Recognition for Transcription of Patient Monitors Using Smartphone Camera-Reference-Cited by-同舟云学术

Using Semi-Automated Annotation and Optical Character Recognition for Transcription of Patient Monitors Using Smartphone Camera

Published:2023-11-09 Issue: Volume: Page:41-46
ISSN:
Container-title:2023 6th International Conference on Digital Medicine and Image Processing
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Author:

Coscolluela IV Jan Federico¹^ORCID,Marasigan Marbert John Chang¹^ORCID,Macalino Joel²^ORCID,Aljibe Miguel²^ORCID,Marcelo Alvin³^ORCID

Affiliation:

1. Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines Manila, Philippines

2. College of Medicine, University of the Philippines Manila, Philippines

3. Medical Informatics Unit, College of Medicine, University of the Philippines Manila, Philippines

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637684.3637691

Reference22 articles.

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2. Saveli I. Goldberg, Andrzej Niemierko, and Alexander Turchin. 2008. Analysis of Data Errors in Clinical Research Databases. AMIA 2008 Symposium Proceedings Page (2008), 242–246.

3. Computer Vision for Continuous Bedside Pharmacological Data Extraction: A Novel Application of Artificial Intelligence for Clinical Data Recording and Biomedical Research

4. Improving Optical Character Recognition Techniques

5. Liu D;Görges M;Jenkins SA; University of Queensland Vital Signs Dataset: Development of an accessible repository of anesthesia patient monitoring data for Research. Retrieved July 21, 2023 from https://pubmed.ncbi.nlm.nih.gov/22190558/