Dr Abhishek Appaji, Ph.D. (A.M.A.)
Research projects
- Principal Investigator for “A Non-intrusive monitoring Smart Bed to generate personalized health profiles using Artificial Intelligence” funded by Department of Science and Technology Oct 2022 onwards.
- Principal Investigator for “Industry Experience R&D Programme to Enhance Learning and build capacity in Medical Technology” funded by Turtle Shell Technologies Pvt Ltd from Feb 2022 to Jan 2027.
- Principal Investigator for “3D printed Kit for the Technology deprived underprivileged to combat COVID19” funded by IEEE Region 10 TENHUMCH2020 from Nov to Dec 2020.
- Principal Investigator for “3D Printed Self Care Kit for Underserved Community in Urban Slums” funded by IEEE HAC/SIGHT from July 2020 to Dec 2020.
- Principal Co-investigator for “Are retinal vascular abnormalities endophenotype in Schizophrenia: An examination in first-degree relative” funded by DST (Jan 2020 onwards).
- Principal co-investigator for “Affordable Trauma Kit during RTA” funded by BIRAC under Biotechnology Ignition grant (Apr 2019 to Apr 2022).
- Project on Device for Intrapartum Materno-fetal care from BIRAC-SRISTI, Govt of India
- Project on A comprehensive fully automated Smart Eye Kiosk for Community Screening (SEKC), from Neg Teng Fong Healthcare Innovation Programme, Singapore
- Project on Development of Low Cost, Safe, High Resolution, Easy to use Digital X-ray from the Department of Science and Technology, Govt of India.
- Consultancy on Mini Mag & I-PCR for from Bhat Biotech Pvt Ltd, India
- Consultancy on Cardio Connect for from Arkav Medtech Pvt Ltd, India
- Retinal Fundus Image as Biomarker for Systemic Disease from BMSCE FRPS
- Consultancy on Wireless Ultrasound Transducer for Monitoring Foetal Heart Rate from Foeto-H, London
Key publications
Appaji, A., Harish, V., Korann, V., Devi, P., Jacob, A., Padmanabha, A., Kumar, V., Varambally, S., Venkatasubramanian, G., Rao, S. V., Suma, H. N., Webers, C. A. B., Berendschot, T. T. J. M., & Rao, N. P. (2022). Deep learning model using retinal vascular images for classifying schizophrenia. Schizophrenia Research, 241, 238-243. https://doi.org/10.1016/j.schres.2022.01.058
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