There are many NLP-based solutions in the healthcare industry that claim to be very accurate and deliver quick results. However, when such systems are implemented in real production scenarios, they end up being low precision, low recall, affecting productivity and hurting company’s bottom line. The task is difficult due to the lack of quality training data and the wide domain expertise needed to succeed.
Episource is building a scalable NLP engine to help summarize medical charts and extract medical coding opportunities and their dependencies to recommend best possible ICD10 codes. Manas Ranjan Kar offers an overview of the wide variety of deep learning algorithms behind Episource’s solution and the complex in-house training-data creation exercises that were required to make it work, focusing on four key motivations for the system. Manas also explains some of the constraints that go into building a deep learning-based clinical decision support system while remaining on the fair side of legal and business guidelines and shares lessons learned building annotation pipelines for training data creation and deep learning frameworks, specifically from the point of view of clinical named entity recognition systems.
Manas Ranjan Kar is a senior manager at US healthcare company Episource, where he leads the NLP and Data Science practice, works on semantic technologies and computational linguistics (NLP), builds algorithms and machine learning models, researches data science journals, and architects secure product backends in the cloud. He has architected multiple commercial NLP solutions in the area of healthcare, food and beverages, finance, and retail. Manas is deeply involved in functionally architecting large-scale business process automation and deep insights from structured and unstructured data using NLP and ML. He has contributed to NLP libraries including Gensim and Conceptnet5 and blogs regularly about NLP on forums like Data Science Central, LinkedIn, and his blog, Unlock Text. Manas speaks regularly about NLP and text analytics at conferences and meetups, such as PyCon India and PyData, has taught hands-on sessions at IIM Lucknow and MDI Gurgaon, and has mentored students from schools including ISB Hyderabad, BITS Pilani, and the Madras School of Economics. When bored, he falls back on Asimov to lead him into an alternate reality.
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