healthcare technology

Neurological disorders such as Parkinson's disease and epilepsy have had some treatment success with deep brain stimulation, but those require surgical device implantation.

A multidisciplinary team at Washington University in St. Louis has developed a new brain stimulation technique using focused ultrasound that is able to turn specific types of neurons in the brain on and off and precisely control motor activity without surgical device implantation.

The team, led by Hong Chen, is the first to provide direct evidence showing noninvasive, cell-type-specific activation of neurons in the brain of mammal by combining ultrasound-induced heating effect and genetics, which they have named sonothermogenetics.

It is also the first work to show that the ultrasound- genetics combination can robustly control behavior by stimulating a specific target deep in the brain.

Results of the three years of research, which was funded in part by the National Institutes of Health's BRAIN Initiative, were published online in Brain Stimulation May 11, 2021.

"Our work provided evidence that sonothermogenetics evokes behavioral responses in freely moving mice while targeting a deep brain site," Chen said. "Sonothermogenetics has the potential to transform our approaches for neuroscience research and uncover new methods to understand and treat human brain disorders."

more at https://medicalxpress.com/news/2021-05-tool-deep-brain-neurons-combining.html

“ATMAN AI”, an Artificial Intelligence algorithm that can detect the presence of COVID-19 disease in Chest X Rays, has been developed to combat COVID fatalities involving lung. ATMAN AI is used for chest X-ray screening as a triaging tool in Covid-19 diagnosis, a method for rapid identification and assessment of lung involvement. This is a joint effort of the DRDO Centre for Artificial Intelligence and Robotics (CAIR), 5C Network & HCG Academics. This will be utilized by online diagnostic startup 5C Network with support of HCG Academics across India.

Triaging COVID suspect patients using X Ray is fast, cost effective and efficient. It can be a very useful tool especially in smaller towns in India owing to lack of easy access to CT scans there.

This will also reduce the existing burden on radiologists and make CT machines which are being used for COVID be used for other diseases and illness owing to overload for CT scans.

The novel feature namely “Believable AI” along with existing ResNet models have improved the accuracy of the software and being a machine learning tool, the accuracy will improve continually.

Chest X-Rays of RT-PCR positive hospitalized patients in various stages of disease involvement were retrospectively analysed using Deep Learning & Convolutional Neural Network models by an indigenously developed deep learning application by CAIR-DRDO for COVID -19 screening using digital chest X-Rays. The algorithm showed an accuracy of 96.73%.

 read more at http://indiaai.gov.in/news/drdo-cair-5g-network-and-hcg-academics-develop-atman-ai