Posts by Malaikannan Sankarasubbu

Advancing Outcomes-Based AI to Interact with Trial Data

Only two months into 2019, Saama is excited to announce a capabilities expansion for its Deep Learning Intelligent Assistant (DaLIA). DaLIA, a context and domain-aware conversational user interface for Saama’s Life Science Analytics Cloud (LSAC), was launched in 2018 and shifted the human-computer interaction paradigm. DaLIA’s new, heightened functionality reinforces Saama’s position as an industry…

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An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text

Adverse reaction caused by drugs is a potentially dangerous problem which may lead to mortality and morbidity in patients. Adverse Drug Event (ADE) extraction is a significant problem in biomedical research. We model ADE extraction as a Question-Answering problem and take inspiration from Machine Reading Comprehension (MRC) literature, to design our model. Our objective in…

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New Frontiers in Data Analytics for Pharma and Healthcare

Data Analytics

Mining Unstructured Texts for Insights using Convolutional Neural Networks Pharmaceutical and Healthcare domains deal with a tremendous amount of unstructured texts, which can be mined effectively using CNN for NLP approach. Malaikannan Sankarasubbu talk about these advanced techniques that can have many applications, such as, building better cohort for clinical trials or establishing better inclusion/exclusion…

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Interpretable Models are the Key to Increased Adoptability of Machine Learning

machine learning

Machine learning has helped drive many technological advancements. There are two models of machine learning, which have their own pros and cons. Malaikannan Sankarasubbu discusses the way interpretable models can increase the machine learning among a wider base of communities. Machine Learning and Deep Learning are responsible for lot of technology advancements in the last…

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Deep Learning and Context Based Intelligent Search


Enterprises have a treasure trove of content in the form of Word documents, pdfs, emails, text files etc . Finding valuable information in these unstructured data has always been difficult. Traditional enterprise search engines have always been about creating indexes for all the words or phrases in the documents and using it to search and…

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