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Prathamesh Karmalkar

Principal Data Scientist at Merck

Prathamesh is an amazing professional, who brings all the skills and expertise in Artificial Intelligence, Natural Language Processing, Text Analytics, Deep Learning & Machine Learning. His capability to do design thinking on applying AI & ML to complex business problems in the area of Healthcare, Life Sciences, Patient Safety, Medical Information, Manufacturing, R&D, etc. is quite impressive. Most of the professionals who worked in the same capacity had to take years to get to learn from experience on how to handle these responsibilities, which seemed natural to him. Prathamesh was selected as Member of Advisory & Technical Committee – International Conference on Next Generation Computing Technologies by Center for Information Technology-UPES for 2015, 2016 & 2017 editions. Currently, Prathamesh is playing Lead Role in Review Committee for NLU, Text Analytics & AI at “International Conference on Machine Intelligence and Data Science Applications (MIDAS) 2020”, 27 – 28 March 2020 in association with IET.

In his current role of Principal Data Scientist & India Lead at Merck Life Sciences, he is bringing thought leadership & expertise to help setup the practice for NLP, Text Analytics, Machine Learning & AI. The idea is to setup R&D labs in Bengaluru under his expertise and mentorship.

All Sessions by Prathamesh Karmalkar

  • Day 2 Bangalore

    January 23, 2020

  • 10:00  - 11:00
    Detecting language nuances from unstructured data could be the difference in serving up the right Google search results or using unsolicited social media chatter to tap into unexplored customer behavior (patients and HCPs). Also, due to the complex regulations and compliances, the Healthcare and Life Sciences industry is known to be slow in adoption of Text analytics and Natural Language Processing. Industries are facing significant challenges in analyzing the data due to its unstructured textual nature. Because of massive digital disruption across the globe, there is sharp rise in the generation of naturally written forms of electronic data. This explosive growth of unstructured clinical data, medical data, regulatory data and healthcare data has prioritized the use of innovative technologies of NLP and Text Analytics. The key challenges in adoption of NLP are – exponential growth in unstructured data in the form of unstructured texts from various business teams within the organization. This ever-growing data remains untouched to identify actionable insights and recommendations that can generate significant value for consumers and patients across the globe. Therefore, detecting potential actions and recommendations from unstructured data could be the key difference in serving up the right insights or deep dive into untouched behavior and actions of physicians and patients. Along with this, the advent in internet and IoT devices are also generating significant amount of data for creating additional value in the market using Natural Language Processing. Many healthcare and life sciences business organizations are progressively moving towards adopting AI driven NLP and Text Analytics capabilities which would help get improved and near-real time insights in unstructured data to derive better results for improved performance across products. This talk will explain our strategy & thought leadership towards adoption of NLP & Text Analytics in Healthcare and Life Sciences industry.
    HALL 2: KNOWLEDGE TALK




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Prathamesh Karmalkar