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Technology Meets Medicine — Disruptive Healthcare Workshop

On the 26th of February, students from all over MAHE assembled at the KMC Interact Hall to attend a two-day seminar by Dronaid, called the Disruptive Healthcare Workshop. Aimed at elicitating the interdisciplinary between medical science and technology — the talks threw light on the potential of artificial intelligence in diagnosis and treatment of diseases for all the future medical specialists. The lectures by various speakers laid significance towards biomimicry using AI to advance the face of medical science.

The first speaker for the evening was Reuben Nellissery, a second-year student from MIT, who opened the forum explaining the advantages of AI merging in with medicine. He explicitly put forth how technical help would reduce the burden on medical staff significantly. Apart from this, he also explained how the speed of medical report interpretation would increase manifolds due to systematic analyzation. Above all this, the most prominent of the incentives was the reduction in human error. With developers and doctors joining hands, a more comfortable and enriching tailor-made treatment process could be made possible for the patients across the globe.

Following this, the participants were introduced to the tiny differences between machine learning and deep learning. Manish Agnihotri, head of the AI Subsystem of Dronaid, took the stage to dwell into a fun and interactive learning session. He explained the various classifications of machine learning while gradually connecting it with mathematics in a way everyone understood. This was a preliminary round to the subsequent one which involved coding. To quote Manish, “Neural network does not model our brain, it is just a basic adaptation of it. One needs to be patient, understanding and calm before jumping into this vast ocean.”

The second day welcomed a satisfactory audience from the previous day as well as newcomers, furthering the Deep Learning algorithms of the last day into real-life applications. The session began with an explanation of algorithms relating to Deep Learning and giving the assemblage an even deeper understanding of the core mechanism of the process. Moving on to discussing practical problems, the speakers took the example of a heart disease and using the principles of logistic regression, demonstrated how one could predict its occurrence. Simple codes were shown for practical problems, with minimal mathematics and technicalities to ensure that people from non-mathematical streams would understand as well.

The session then tackled the primary case study of the event – breast cancer (benign or malignant). Using a given sample of information, it was discussed how deep learning facilitates its prediction. Urging input from the audience as well, a KMC intern gave an excellent explanation of the biological details of breast cancer. The lecturer made good use of the slides as well as the blackboard to paint a clear picture of the algorithm, explaining the concept at every step. Following a short talk on Neural Networks and their multiple types, the discussion shifted to an in-depth introduction to IBM’s Watson AI Healthcare Programme, elucidating its use of cognitive computing and complex evidence-based approach to develop inherent reasoning abilities. A video of IBM Watson Health Cloud was shown after the explanation, showing how technology has reached far enough to make smart devices that can measure a person’s heart rate, sleeping patterns, and even walking habits, thereby drawing insightful conclusions of the person’s health.

With a lot of matter to speak on, the event stretched to nearly three hours, but with no complaints from the audience, who were only left wanting more. The organisers urged the Healthcare workshop majorly towards KMC students to ignite within them the idea of combining biological discoveries with cutting-edge technology to provide the most optimum healthcare situations possible. The workshop was beautifully carried out and served a good point of bridging the gap between technology and medicine, all to create the strongest results for humanity now, and in the future.

Photo Credits: Ankit Varshney 

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