Mobile U-Health Service System for Personalized Diagnosis Based on Ontology

Min, Byung-Won

doi:10.1007/978-3-642-32692-9_31

Cited by 2 publications

(2 citation statements)

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“…Finally, in (Min 2012), Min introduced an ontology-based personalized disease method employing the machine learning technique and effectively assigning the weight factors to the disease-related variables. The impact of this development is prominent and allows medical checkups and other related services to be delivered without requiring visits to medical agencies.…”

Section: Introductionmentioning

confidence: 99%

“…The impact of this development is prominent and allows medical checkups and other related services to be delivered without requiring visits to medical agencies. The proposed Personalized Computer Aided Diagnosis Probability (PCADP) algorithm described in (Min 2012) is a personalized statistical disease prediction method. Using the bio signals, types and forms of the physical symptoms and weight factors of a disease that are acquired by the individual as a feedback and applying the embedded components of data management, analysis and decision-making support makes possible to diagnose the presence or not of a disease in the subject.…”

Section: Introductionmentioning

confidence: 99%

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M-health: supporting automated diagnosis and electonic health records

Alepis

Lambrinidis

2013

SpringerPlus

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BackgroundMobile technology has become a part of our everyday life. Mobile services are used in a wide variety of scientific areas including healthcare. As an intersection of computer supported technology and medicine, m-health is expected to bring higher quality in healthcare. A remedy to deter people from neglecting their health issues is providing further and targeted information, while this information is available on the main devices most people use on a regular basis, namely any station or a mobile phone connected to Internet, enabling access to their health status anytime and at any place.ResultsThe authors present a framework that is built based on mobile health and which, in addition, incorporates a module that is responsible for making diagnoses. To achieve this, we have applied the Analytical Hierarchical Process algorithm (AHP) on the test results, making the system able to infer the presence or not of an illness in the subject. Data to be processed emerge from the corresponding subjects’ electronic health records. Through the resulting system, doctors and health companies, which are involved in medical sciences, are offered a sophisticated, powerful tool that provides supplementary diagnoses about their clients by employing their laboratory medical tests.ConclusionsIn this paper a novel computer supported framework is presented, which is targeted basically in the scientific area of mobile health. The incorporated medical diagnosis module and the online presentation of medical tests results may not only facilitate doctors’ and medical agencies work and support healthcare in general, but also and most importantly can benefit users by having an analytical picture of their health status at any place and time. Perhaps one of the most challenging targets for this system to reach is to draw individuals’ attention and give them motives to be more concerned about their health.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%