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Helping machines to understand human language better

Natural language is ambiguous. Human beings can easily disambiguate the meaning of linguistic units such as words, phrases and sentences as they read or listen. However it is difficult for machines to do the same without explicit representations of syntax, semantic and discourse. As a researcher in Natural Language Processing (NLP) at NTU, Professor Joty

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Developing a unified framework for NLP algorithms

Natural language processing (NLP) has been around for more than 50 years but has become more well-known recently, thanks to personal assistant applications such as Apple’s Siri and Amazon’s Alexa. It is also the driving force behind language translation applications such as Google Translate. It has been no easy feat coming this far. Enabling computers

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Natural Language Processing for Appendicitis Diagnosis

Researchers in natural language processing (NLP) have made significant progress recently. We have also witnessed more NLP applications in widespread use, such as chatbots, grammar checkers and more. One emerging application is medical text mining, which involves the use of NLP algorithms to process clinical notes written by doctors, to derive useful information and knowledge.

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Mobilizing AI for Health on a Global Scale

AI has the potential to transform how healthcare is delivered. In a 2019 Future Health Index survey by Philips, Singapore came in third in the use of AI in healthcare, where most AI applications are used to improve clinical diagnostic accuracy. In June 2018, AI Singapore launched our inaugural AI in Health Grand Challenge to

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