NLP Powered Doctor-Patient Video Conferencing
People have been using remote and on-demand medicine ever since the advent of the COVID-19 pandemic and developments in modern communication technologies. As remote medicine becomes more common, many people are choosing to be treated from home rather than traveling for treatment. This increase of interest in remote medicine promotes a synthesis between digital communication and traditional methods of care and diagnosis.
Remote medical video tele-consultation can be simple to set up as long as it is designed in such a way that there will be no delay or interference during the conversation between doctor and patient. This means we need to create a conferencing system that could be stable yet feature-rich and simple for both the doctor and patient to use.
New Delhi, India
Client
Healthcare IT Services & Customer Relations
CLIENT
Embebo.com, a healthcare-focused IT services and consulting company based in India, offers hospitals and clinics the best customer relationship management and records retention solutions available. Embebo provides modules and tools that can help organize your medical records, notes, and opinions with seamless integration, efficient control — and enhanced insights.
We were tasked by Embebo to create a tool that could facilitate communication between doctor and patient seamlessly and without any discrepancies. Embebo needed us to create an in-house solution since that would be beneficial as an one-stop solution within their already existing customer base.
CHALLENGE
Our implementation needs to tackle these challenges at first:
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Creation of Proper Communication Channels - Creating an in-house online communications channel would be a grueling task since it needs high degree of back-end setup.
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Conversation Tracking - The data used had to be truthful and distinct; irrelevant, redundant, and fake data could be extremely harmful for our prediction model.
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End to End Security - Client security is very important since medical diagnostics contain important personal information.
SOLUTION
We drafted a concept-oriented plan to tackle these challenges:
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LueinAnalytics proposes the creation of a web-socket that would allow seamless communication between doctor and patient.
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A Natural Language Processing (NLP) tool is also integrated into this system, which could extract specific and important medical details from patients’ speech or written responses.
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This makes it easier for us to refer back to the conference to identify any critical ailments or concerns.
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This NLP-based conferencing system helps the doctor provide a more accurate diagnosis and treatment plan by analyzing every aspect of the conversation.
RESULT
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With a secure conferencing application such as this, it is would be very easy for both the doctors and patients to engage in healing conversation anywhere anytime.
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Its safety, transcripting rates, and ease of access would be phenomenal for the client and their customers.
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An on-demand service like this quite valuable for Embebo in the long run and could elevate it position to a market leader since remote medicine will develop further in the future consistently.