Automated Categorization of Systemic Disease and Duration From Electronic Medical Record System Data Using Finite-State Machine Modeling: Prospective Validation Study
BackgroundOne of the major challenges in the health care sector is that approximately 80% of generated data remains unstructured and unused. Since it is difficult to handle unstructured data from electronic medical record systems, it tends to be neglected for analyses in most hospitals and medical c...
Main Authors: | Sai Prashanthi, Gumpili, Deva, Ayush, Vadapalli, Ranganath, Das, Anthony Vipin |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2020-12-01
|
Series: | JMIR Formative Research |
Online Access: | http://formative.jmir.org/2020/12/e24490/ |
Similar Items
-
Forecast of Outpatient Visits to a Tertiary Eyecare Network in India Using the EyeSmart Electronic Medical Record System
by: Gumpili Sai Prashanthi, et al.
Published: (2021-06-01) -
Prevalence of chronic disease in older adults in multitier eye-care facilities in South India: Electronic medical records-driven big data analytics report
by: Umesh Chandra Behera, et al.
Published: (2021-01-01) -
Leveraging big data for pattern recognition of socio-demographic and climatic factors in correlation with eye disorders in Telangana State, India
by: Amna Alalawi, et al.
Published: (2021-01-01) -
Automated document preprocessing for text categorization
by: Abd Rahman, Suraya, et al.
Published: (2006) -
Design automation for partially reconfigurable adaptive systems
by: Kizheppatt, Vipin
Published: (2015)