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Finding Patients At Risk for Rare Disease

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Extracting Electronic Health Record (EHR) Data Using Transfer Learning

January 9, 2023 by Corey Fournier, Senior Data Engineer

At ThinkGenetic, Inc. our goal is to reduce the time to diagnosis for genetic and rare conditions. Given they are rare, we must be cognizant of the time it takes […]

News, Technical Research algorithms, BERT model, clinical note, EHR, electronic health records, genetic conditino, genetic condition, Google, ICD-10, Medical Coding, medical record, misdiagnosed, Name Entity Recognition, Natural Language Processing, NLP, Procedures codes, Rare Disease, rare genetic disease, Relation Extraction, Semantic Role labeling, Shi and Lin, Snomed, structured data, T5, Text-to-text Transfer Transformers, undiagnosed, unstructured data

Application of Natural Language Processing in Clinical Applications

October 14, 2021 by Sarika Kondra

Natural Language Processing is a field of computational linguistics, computer science and more specially artificial intelligence (AI) that uses statistics, machine learning (ML) and deep learning (DL) techniques to understand […]

News, Technical Research AI, artificial intelligence, big data, data, De-identification of records, dependency parsing, lemmatization, Named Entity Recognition, Natural Language Processing, Negation Detection, NLP, part-of-speech, Part-of-Speech Tagging, POS Tagging, Relation Extraction, Sarika Kondra, Sentence Tokenization, stemming, Stemming and Lemmatization, tokenization, unstructured data, Word Tokenization

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