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Vol. 2 No. 01 (2015)
Volume 02 Issue 01

Articles

VISIONARY DIAGNOSIS: MACHINE LEARNING'S ROLE IN DETECTING DIABETIC RETINOPATHY FOR PRECISION HEALTHCARE

Published 2015-06-13

  • Bharti Rai

Bharti Rai
Department of Computer Science and Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur, India

Abstract

Diabetic retinopathy (DR) is a prevalent complication of diabetes mellitus and a leading cause of blindness worldwide. Timely detection and intervention are critical to prevent vision loss. This study explores the transformative role of machine learning in the diagnosis of diabetic retinopathy, emphasizing its potential to enhance precision healthcare. Leveraging a vast dataset of retinal images, we employ advanced machine learning algorithms to develop a robust and accurate diagnostic model. Our findings highlight the promise of machine learning as a tool for early DR detection, paving the way for proactive and personalized patient care.

Keywords

Diabetic retinopathy, Machine learning, Diagnosis

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References

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