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Advanced medical imaging technology wins Omnis Award

BrainsightAI is a deep tech health startup that aims to help neurosurgeons and neuro radiologists pre-plan oncological surgeries to preserve functionality of their patient.

China grants emergency approval for its first Covid drug
The most effective treatment for Covid currently involves monoclonal antibodies, which are administered via a drip - Copyright GETTY IMAGES NORTH AMERICA/AFP/File Go Nakamura
The most effective treatment for Covid currently involves monoclonal antibodies, which are administered via a drip - Copyright GETTY IMAGES NORTH AMERICA/AFP/File Go Nakamura

Medical imaging technology continues to advance, leading to faster and more accurate medical diagnoses to be made. There are several examples of investigations leveraging computer-aided diagnostics providing improved accuracy, sensitivity, and specificity for the detection of different diseases when compared with conventional methods.

An example of such technology has been recognised by the industry. BrainsightAI is a deep tech health startup that aims to help neurosurgeons and neuro radiologists pre-plan oncological surgeries to preserve functionality of their patient.

The company has recently been awarded the Omnis Award for Asynchronous and Hybrid Working. The awards single-out employees and employers who have adapted to a new normal of working remotely, with teams situated globally.

BrainsightAI works with diagnostics and treatment of neuropsychiatric disorders in order to support medics and to speed up the diagnosis time through automation. The current, symptom-based approach to diagnosis that many medics need to follow is time consuming and vulnerable to misdiagnosis.

The dangers here is that such approaches lead to a worsening of the condition. In contrast, with the technology neurologists can examine 3D simulations to aid their understanding as to which parts of the brain are affected by a given condition.

Brainsight’s approach is to shift the approach from symptom-reliant to imaging-based diagnosis, which is faster, easier, and more accurate. The use of machine-learned models has the potential to identify biological markers and delineate symptom clusters.

The Asynchronous & Hybrid Working Omni award recognized the efforts to perform a complete overhaul from an in-person, synchronous business to a fully hybrid, asynchronous model.

According to The Omnis judges: “The pandemic stopped all face-to-face contact as well as provided a roadblock to the people they needed to talk to in order to address the more immediate medical crisis. To still get there by adapting all of their processes and building software to enable them to work remotely with each of these stakeholders is an amazing achievement. They say even now the development team has never met face-to-face.”

There is a scientific basis to the technology with Dr. Rimjhim Agrawal, co-founder and CTO, BrainSightAI, having co-authored two papers in the Nature journal relating to the application of the technology yin diagnosing schizophrenia.

Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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