Research title: Development and validation of artificial intelligence based deep learning algorithm for the prediction of systemic and ocular abnormalities from retinal optical coherence tomography and fundus photographs.
Supervisor: Dr Maitreyee Roy
Co-supervisors: Dr Vinod Maseedupally, Dr Rajiv Raman
Research Abstract:
In recent years, ophthalmology has seen incredible progress in high-resolution imaging techniques. Retinal photography and optical coherence tomography (OCT) are now comm...
Research title: Development and validation of artificial intelligence based deep learning algorithm for the prediction of systemic and ocular abnormalities from retinal optical coherence tomography and fundus photographs.
Supervisor: Dr Maitreyee Roy
Co-supervisors: Dr Vinod Maseedupally, Dr Rajiv Raman
Research Abstract:
In recent years, ophthalmology has seen incredible progress in high-resolution imaging techniques. Retinal photography and optical coherence tomography (OCT) are now commonly used in eye hospitals and for screening purposes. These imaging methods are highly valuable in diagnosing eye conditions, but they also show promise in identifying signs of systemic diseases. While we have made significant strides in understanding the relationship between the eye and the body using traditional statistical models, the use of artificial intelligence (AI) in treating critical disorders is still in its early stages.
Our project’s aim is to develop and validate a deep-learning model that can predict systemic diseases using retinal OCT and fundus photographs. By leveraging AI, we aim to advance medical innovation and transform the way these conditions are diagnosed and managed.
Through this research, we hope to uncover hidden insights within ocular imaging data and gain a better understanding of how the eye can provide indications of systemic diseases. In this era of technological advancements, we envision a future where ocular assessments play a vital role in detecting and monitoring systemic diseases. Our research goal is to revolutionize healthcare by using the eye as a window into overall health, ultimately enhancing patient well-being.
Biography
Rehana Khan Tajuddin Mohamed Akthar Khan is a PhD candidate at the School of Optometry and Vision Science (SOVS), UNSW. Her research focuses on utilizing artificial intelligence algorithms for the prediction of ocular and systemic diseases. With a BS Optometry degree from the Elite School of Optometry, India, she has valuable experience as a clinical and research optometrist. Rehana has made notable contributions through her published works and peer-reviewed journal reviews. Alongside her PhD studies, she also serves as an associate lecturer, imparting her knowledge and expertise in Optics courses to undergraduate optometry students at UNSW.
Education:
PhD Student at UNSW, School of Optometry and Vision Science, 2022- current
Bachelor of Optometry and Vision Science, Elite School of Optometry & Birla Institute of Technology and Science (BITS), India, 2015
Conference attendance:
Khan, R. (2019). Revised Glycemic index for diagnosis and monitoring of diabetes mellitus in South Indian population. ARVO-INDIA, 26th Indian Eye Research Group Meeting.
Raman, R., Saha, S., Frost, S., Khan, R., Sharma, T., & Kanagasingam, Y. (2020). Assessment of vessel parameters as a micro vascular biomarker using a retinal vessel analysis system (VASP). Investigative Ophthalmology & Visual Science, 61(7), 496-496. ARVO annual meet 2020.
Khan, R., Chandra, S., Ramachandran, R., Rani, P. K., Anantharaman, G., Sen, A., ... & Raman, R. (2020). A collaborative multicenter retrospective study on the prevalence and incidence of visual impairment and blindness in patients presenting with active proliferative diabetic retinopathy in India. Investigative Ophthalmology & Visual Science, 61(7), 3825-3825. ARVO annual meet 2020.
Rizza, A. N., Susarla, G., Khan, R., Wang, V., Brustoski, K., Sarangapani, S., ... & Sobrin, L. (2020). Risk factors for proliferative diabetic retinopathy and diabetic macular edema in the South Indian population. Investigative Ophthalmology & Visual Science, 61(7), 4842-4842. ARVO annual meet 2020.
Han S, Rizza AN, Khan R, Li A, Chan W, Susarla G, Lains I, Brustoski K, Khetan V, Raman R, Iyengar SK. Risk factors for optical coherence tomography-assessed center-involving diabetic macular edema in a South Indian population. Investigative Ophthalmology & Visual Science. 2021 Jun 21;62(8):1127-. ARVO annual meet 2021.
Khan, R. (2021). Association Between Gut Microbial Abundance and Sight-Threatening Diabetic Retinopathy. 2nd IVI International Optometry Conference, 2021.
Awards:
Best poster presentation award in the 2nd India Vision Institute (IVI) International Optometry Conference, 2021
University Postgraduate Award (Stipend for 2022 - 2025), UNSW
UNSW School of Optometry and Vision Science: Diabetes Research Grant from the Elizabeth O’Beirne and Robert and Emmy Mather Trust Fund, 2023
Mentee, Industry Mentoring Network in STEM (IMNIS), 2023
Affiliations and memberships:
2020-present: Association of Research in Vision and Ophthalmology (ARVO), member-in-training
2022-present: American Academy of Optometry (AAO)
2022-present: Member of Vision Science Academy
