Diabetic Retinopathy Analysis

Sivakumar, R.; Ravindran, G.; Muthayya, M; Lakshminarayanan, S.; Velmurughendran, C. U.

doi:10.1155/jbb.2005.20

Cited by 20 publications

(11 citation statements)

References 55 publications

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“…Also, prognosis of the condition can be determined during the treatment. 13 In the present study, the mean P100 latency in the diabetics was found to be significantly prolonged (105.34±7.11SD) when compared with those in the controls (98.21±0.96 SD) ( Table 4). The above findings are in accordance with similar studies in the past including either Type 1 or Type 2 DM or both, without retinopathy.…”

Section: Discussionsupporting

confidence: 51%

Visual evoked potential changes in patients with diabetes mellitus without retinopathy

Gupta¹,

Gupta²,

Deshpande

2015

Int J Res Med Sci

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Section: Discussionsupporting

confidence: 51%

Visual evoked potential changes in patients with diabetes mellitus without retinopathy

Gupta¹,

Gupta²,

Deshpande

2015

Int J Res Med Sci

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“…In reviewing the literature on retinal image analysis, most progress is in the automated grading process with the goal of replacing the high resources used in current manual grading. In general, the use of computers to aid the detection of retinopathy has been accomplished in as many different ways as there are groups performing the work 90–101 . The use of neural networks that try and ‘teach’ computing systems to recognise patterns has not yet achieved a high enough sensitivity and specificity to be used The simplest algorithms are those that differentiate between a disease and a no disease state.…”

Section: Vision and Challenges For The Futurementioning

confidence: 99%

Telemedicine and ocular health in diabetes mellitus

Bursell

Brazionis

Jenkins

2012

Clinical and Experimental Optometry

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Teleretinal/teleophthalmological programs that use existing health information technology infrastructure solutions for people with diabetes increase access to and adherence to appropriate eye care. Teleophthalmological studies indicate that the single act of patients viewing their own retinal images improves self-management behaviour and clinical outcomes. In some settings this can be done at lower cost and with improved visual outcomes compared with standard eye care. Cost-effective and sustainable teleretinal surveillance for detection of diabetic retinopathy requires a combination of an inexpensive portable device for taking low light-level retinal images without the use of pharmacological dilation of the pupil and a computer-assisted methodology for rapidly detecting and diagnosing diabetic retinopathy. A more holistic telehealth-care paradigm augmented with the use of health information technology, medical devices, mobile phone and mobile health applications and software applications to improve health-care co-ordination, self-care management and education can significantly impact a broad range of health outcomes, including prevention of diabetes-associated visual loss. This approach will require a collaborative, transformational, patient-centred health-care program that integrates data from medical record systems with remote monitoring of data and a longitudinal health record. This includes data associated with social media applications and personal mobile health technology and should support continuous interactions between the patient, health-care team and the patient's social environment. Taken together, this system will deliver contextually and temporally relevant decision support to patients to facilitate their well-being and to reduce the risk of diabetic complications.

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“…[135][136][137] Results of automated grading to diagnose retinopathy have also been mixed, although some approaches have produced encouraging results. [138][139][140][141] Risks in adopting computer-aided retinopathy detection include unknown algorithm lesion sensitivity and specificity, the possibility of false negatives, and/or missed referable cases.…”

Section: Appendix 3: Computer-aided Detectionmentioning

confidence: 99%

Telehealth Practice Recommendations for Diabetic Retinopathy, Second Edition

Horton

Bursell

et al. 2011

Telemedicine and e-Health

111

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Ocular telemedicine and telehealth have the potential to decrease vision loss from DR. Planning, execution, and follow-up are key factors for success. Telemedicine is complex, requiring the services of expert teams working collaboratively to provide care matching the quality of conventional clinical settings. Improving access and outcomes, however, makes telemedicine a valuable tool for our diabetic patients. Programs that focus on patient needs, consider available resources, define clear goals, promote informed expectations, appropriately train personnel, and adhere to regulatory and statutory requirements have the highest chance of achieving success.

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Diabetic Retinopathy Analysis

Cited by 20 publications

References 55 publications

Visual evoked potential changes in patients with diabetes mellitus without retinopathy

Visual evoked potential changes in patients with diabetes mellitus without retinopathy

Telemedicine and ocular health in diabetes mellitus

Telehealth Practice Recommendations for Diabetic Retinopathy, Second Edition

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