a-multifunctional-embedded-based-bluetooth-enabled-programmable

A Multifunctional, Embedded-based, Bluetooth-enabled, Programmable, Biphasic-waveform Stimulator with Real-time Neural Signal Acquisition

The study introduces a lightweight, Bluetooth-enabled deep brain stimulation (DBS) device that is designed specifically for preclinical research in small, ...

Christ College of Engineering

Deep learning is a prominent method for automatic detection of COVID-19 disease using a medical dataset. This paper aims to give a perspective on the data insufficiency issue that exists in COVID-19 detection associated with deep learning. The extensive study of the available datasets comprising CT and X-ray images is presented in this paper, which can be very much useful in the context of a deep learning framework for COVID-19 detection. Moreover, various data handling techniques that are very essential in deep learning models are discussed in detail. Advanced data handling techniques and approaches to modify deep learning models are suggested to handle the data insufficiency problem in deep learning based on COVID-19 detection.

Caren Babu

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