ArticleJournal of medical systems2016
A mobile decision support system for red eye diseases diagnosis: experience with medical students.
Article in Journal of medical systems, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 26 citations in OpenAlex.
- A Systematic Review of Factors Affecting Utilization of Decision Support Systems: The Interplay Between Technology, Users, and the Healthcare Environment.Health science reports · 2026Review
- Artificial intelligence virtual assistants in primary eye care practice.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025Article
- An intelligent decision support system for acute postoperative endophthalmitis: design, development and evaluation of a smartphone application.BMC medical informatics and decision making · 2023Article
- A clinical decision support system for diagnosing and determining severity of dry eye disease.Eye (London, England) · 2023Article
- Usability Methods and Attributes Reported in Usability Studies of Mobile Apps for Health Care Education: Scoping Review.JMIR medical education · 2022Article
- A mobile app for Glaucoma diagnosis and its possible clinical applications.BMC medical informatics and decision making · 2020Article
- mHealth App for iOS to Help in Diagnostic Decision in Ophthalmology to Primary Care Physicians.Journal of medical systems · 2017Article
- Android mobile applications in eye care.Oman journal of ophthalmologyReview
- Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A good primary health care is the base for a better healthcare system. Taking a good decision on time by the primary health care physician could have a huge repercussion. In order to ease the diagnosis task arise the Decision Support Systems (DSS), which offer counselling instead of refresh the medical knowledge, in a profession where it is still learning every day. The implementation of these systems in diseases which are a frequent cause of visit to the doctor like ophthalmologic pathologies are, which affect directly to our quality of life, takes more importance. This paper aims to develop OphthalDSS, a totally new mobile DSS for red eye diseases diagnosis. The main utilities that OphthalDSS offers will be a study guide for medical students and a clinical decision support system for primary care professionals. Other important goal of this paper is to show the user experience results after OphthalDSS being used by medical students of the University of Valladolid. For achieving the main purpose of this research work, a decision algorithm will be developed and implemented by an Android mobile application. Moreover, the Quality of Experience (QoE) has been evaluated by the students through the questions of a short inquiry. The app developed which implements the algorithm OphthalDSS is capable of diagnose more than 30 eye's anterior segment diseases. A total of 67 medical students have evaluated the QoE. The students find the diseases' information presented very valuable, the appearance is adequate, it is always available and they have ever found what they were looking for. Furthermore, the students think that their quality of life has not been improved using the app and they can do the same without using the OphthalDSS app. OphthalDSS is easy to use, which is capable of diagnose more than 30 ocular diseases in addition to be used as a DSS tool as an educational tool at the same time.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.