Technologies

Medical Sciences

Title:

A Java based low-cost user friendly stand alone as well client-server architecture computer aided system for diagnosis of middle ear pathologies based on a hybrid learning framework using videos captured through digital otoscope with camera

Area:

Medical Sciences

Focus Area:

Healthcare, Digital Health

Status:

Proof of concept

Social Benefits:

The proposed system be used by general practitioners, otolaryngology specialist or healthcare professionals to provide them a second objective opinion about diagnosis of middle ear pathologies, help them to make more accurate diagnosis using a low-cost system based on a hybrid learning framework.

Developing Agency:

Kavitha S Murugesan, Chennai, Tamil Nadu

Technology Readiness Index:

TRL4 Complete

Source Title:

Data sourced from Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology (DBT)

Brief Description

Description :

The hybrid learning model exploit the ability of CNNs to extract deep features as well as LSTM networks to learn hidden patterns in spatial sequential data i.e., from videos .

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