Papers & Conferences

Peer-reviewed academic papers and talks at prominent Data, AI and NLP Events

 

Biomedical Named Entity Recognition at Scale

November 2020
Authors: Veysel Kocaman, David Talby
Accepted to CADL 2020 (International Workshop on Computational Aspects of Deep Learning) , organized in conjunction with ICPR 2020

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Named entity recognition (NER) is a widely applicable natural language processing task and building block of question answering, topic modeling, information retrieval, etc. In the medical domain, NER plays a crucial role by extracting meaningful chunks from clinical notes and reports, which are then fed to downstream tasks like assertion status detection, entity resolution, relation extraction, and de-identification.
Reimplementing a Bi-LSTM-CNN-Char deep learning architecture on top of Apache Spark, we present a single trainable NER model that obtains new state-of-the-art results on seven public biomedical benchmarks without using heavy contextual embeddings like BERT. This includes improving BC4CHEMD to 93.72% (4.1% gain), Species800 to 80.91% (4.6% gain), and JNLPBA to 81.29% (5.2% gain).

Improving Clinical Document Understanding on COVID-19 Research with Spark NLP

December 2020
Authors: Veysel Kocaman, David Talby
Accepted to SDU (Scientific Document Understanding) workshop at AAAI 2021

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Following the global COVID-19 pandemic, the number of scientific papers studying the virus has grown massively, leading to increased interest in automated literate review. We present a clinical text mining system that improves on previous efforts in three ways.
First, it can recognize over 100 different entity types including social determinants of health, anatomy, risk factors, and adverse events in addition to other commonly used clinical and biomedical entities. Second, the text processing pipeline includes assertion status detection, to distinguish between clinical facts that are present, absent, conditional, or about someone other than the patient. Third, the deep learning models used are more accurate than previously available, leveraging an integrated pipeline of state-of-the-art pretrained named entity recognition models, and improving on the previous best performing benchmarks for assertion status detection.

Spark NLP: Natural language understanding at scale

 January 2021
Authors: Veysel Kocaman, David Talby
Accepted to Software Impact Journal Elseiver

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Spark NLP is a Natural Language Processing (NLP) library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines that can scale easily in a distributed environment.
Spark NLP comes with 1100+ pretrained pipelines and models in more than 192+ languages. It supports nearly all the NLP tasks and modules that can be used seamlessly in a cluster. Downloaded more than 2.7 million times and experiencing 9x growth since January 2020, Spark NLP is used by 54% of healthcare organizations as the world’s most widely used NLP library in the enterprise.

Automating Clinical Data Abstraction From Unstructured Documents Using Spark NLP

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May, 2021
Speaker: David Talby

State-of-the-art Emotion and Sentiment Analysis with Spark NLP

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November 18th, 2020
Speaker: Dia Trambitas

Automated Detection of Environmental, Social, and Governance Issues in Financial Documents

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December 10, 2020
Speaker: Alina Petrukhova

Automated and Explainable Deep Learning for Clinical Language Understanding at Roche

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August, 2020
Speaker: David Talby, PhD

How to Apply State-of-the-Art Natural Language Processing in Healthcare

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August, 2020
Speaker: David Talby, PhD

Using Spark NLP to Enable Real-World Evidence (RWE) and Clinical Decision Support in Oncology

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April 13 - April 17, 2020
Speaker: Veysel Kocaman, PhD

Applying State-of-the-art Natural Language Processing for Personalized Healthcare

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April 13 - April 17, 2020
Speakers: David Talby, PhD

Spark NLP for Healthcare: Lessons Learned Building Real-World Healthcare AI Systems

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April 13 - April 17, 2020
Speaker: Veysel Kocaman, PhD

State-of-the-art Natural Language Processing at Scale

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April 13 - April 17, 2020
Speakers: David Talby, PhD

Apache SPARK NLP: Extending SPARK ML to Deliver Fast, Scalable & Unified Natural Language Processing

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Spark + AI summit

June 4 - June 6, 2018
Speakers: David Talby, PhD

State of the Art Natural Language Processing at Scale

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Spark + AI summit

June 4 - June 6, 2018

Speakers: David Talby, PhD


State of the Art Natural Language Processing at Scale

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October 26 - October 30, 2018
Speakers: David Talby, PhD

Spark NLP in Action: Learning to read Life Science research

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Data Science Summit 2018
May 28, 2018
Speakers: Saif Addin Ellafi

Natural Language Understanding at Scale with Spark-Native NLP, Spark ML, and TensorFlow

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spark summit europe

October 24 - October 26, 2017
Speakers: Alexander Thomas