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1
Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network
Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network
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Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network

BMC medical informatics and decision making, 2023-10, Vol.23 (1), p.1-216, Article 216 [Peer Reviewed Journal]

COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;BioMed Central Ltd., part of Springer Nature 2023 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-023-02301-5 ;PMID: 37833661

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2
Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers
Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers
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Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers

BMC medical informatics and decision making, 2021-09, Vol.21 (1), p.1-262, Article 262 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01623-6 ;PMID: 34511100

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3
A systematic review of natural language processing applied to radiology reports
A systematic review of natural language processing applied to radiology reports
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A systematic review of natural language processing applied to radiology reports

BMC medical informatics and decision making, 2021-06, Vol.21 (1), p.179-179, Article 179 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01533-7 ;PMID: 34082729

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4
A bibliometric analysis of natural language processing in medical research
A bibliometric analysis of natural language processing in medical research
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A bibliometric analysis of natural language processing in medical research

BMC medical informatics and decision making, 2018-03, Vol.18 (Suppl 1), p.14-14, Article 14 [Peer Reviewed Journal]

COPYRIGHT 2018 BioMed Central Ltd. ;The Author(s). 2018 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-018-0594-x ;PMID: 29589569

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5
A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine
A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine
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A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine

BMC medical informatics and decision making, 2021-02, Vol.21 (1), p.69-69, Article 69 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01395-z ;PMID: 33618727

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6
Prediction of adverse drug reactions based on knowledge graph embedding
Prediction of adverse drug reactions based on knowledge graph embedding
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Prediction of adverse drug reactions based on knowledge graph embedding

BMC medical informatics and decision making, 2021-02, Vol.21 (1), p.38-11, Article 38 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01402-3 ;PMID: 33541342

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7
A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora
A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora
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A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora

BMC medical informatics and decision making, 2022-09, Vol.22 (1), p.1-235, Article 235 [Peer Reviewed Journal]

COPYRIGHT 2022 BioMed Central Ltd. ;2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-022-01967-7 ;PMID: 36068551

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8
Transformers-sklearn: a toolkit for medical language understanding with transformer-based models
Transformers-sklearn: a toolkit for medical language understanding with transformer-based models
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Transformers-sklearn: a toolkit for medical language understanding with transformer-based models

BMC medical informatics and decision making, 2021-07, Vol.21 (Suppl 2), p.1-90, Article 90 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01459-0 ;PMID: 34330244

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9
Transformer-based deep neural network language models for Alzheimer's disease risk assessment from targeted speech
Transformer-based deep neural network language models for Alzheimer's disease risk assessment from targeted speech
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Transformer-based deep neural network language models for Alzheimer's disease risk assessment from targeted speech

BMC medical informatics and decision making, 2021-03, Vol.21 (1), p.92-92, Article 92 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01456-3 ;PMID: 33750385

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10
Intelligent virtual case learning system based on real medical records and natural language processing
Intelligent virtual case learning system based on real medical records and natural language processing
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Intelligent virtual case learning system based on real medical records and natural language processing

BMC medical informatics and decision making, 2022-03, Vol.22 (1), p.60-60, Article 60 [Peer Reviewed Journal]

2022. The Author(s). ;COPYRIGHT 2022 BioMed Central Ltd. ;The Author(s) 2022 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-022-01797-7 ;PMID: 35246134

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11
Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods
Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods
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Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods

BMC medical informatics and decision making, 2021-04, Vol.21 (1), p.128-128, Article 128 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-021-01487-w ;PMID: 33858409

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12
Exploring the potential of ChatGPT in medical dialogue summarization: a study on consistency with human preferences
Exploring the potential of ChatGPT in medical dialogue summarization: a study on consistency with human preferences
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Exploring the potential of ChatGPT in medical dialogue summarization: a study on consistency with human preferences

BMC medical informatics and decision making, 2024-03, Vol.24 (1), p.75-75 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-024-02481-8 ;PMID: 38486198

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13
Assessing the research landscape and clinical utility of large language models: a scoping review
Assessing the research landscape and clinical utility of large language models: a scoping review
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Assessing the research landscape and clinical utility of large language models: a scoping review

BMC medical informatics and decision making, 2024-03, Vol.24 (1), p.72-72 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-024-02459-6 ;PMID: 38475802

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14
Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment
Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment
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Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment

BMC medical informatics and decision making, 2024-02, Vol.24 (1), p.40-40 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-024-02444-z ;PMID: 38326769

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15
ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports
ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports
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ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports

BMC medical informatics and decision making, 2023-11, Vol.23 (1), p.262-262, Article 262 [Peer Reviewed Journal]

2023. The Author(s). ;COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-023-02369-z ;PMID: 37974186

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16
Automatic data extraction to support meta-analysis statistical analysis: a case study on breast cancer
Automatic data extraction to support meta-analysis statistical analysis: a case study on breast cancer
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Automatic data extraction to support meta-analysis statistical analysis: a case study on breast cancer

BMC medical informatics and decision making, 2022-06, Vol.22 (1), p.1-158, Article 158 [Peer Reviewed Journal]

COPYRIGHT 2022 BioMed Central Ltd. ;2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-022-01897-4 ;PMID: 35717167

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17
A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals
A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals
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A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals

BMC medical informatics and decision making, 2024-04, Vol.24 (1), p.107-107 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-024-02506-2 ;PMID: 38654295

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18
Text mining and portal development for gene-specific publications on Alzheimer's disease and other neurodegenerative diseases
Text mining and portal development for gene-specific publications on Alzheimer's disease and other neurodegenerative diseases
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Text mining and portal development for gene-specific publications on Alzheimer's disease and other neurodegenerative diseases

BMC medical informatics and decision making, 2024-04, Vol.24 (Suppl 3), p.98-98 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-024-02501-7 ;PMID: 38632621

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19
Using artificial intelligence to identify patients with migraine and associated symptoms and conditions within electronic health records
Using artificial intelligence to identify patients with migraine and associated symptoms and conditions within electronic health records
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Using artificial intelligence to identify patients with migraine and associated symptoms and conditions within electronic health records

BMC medical informatics and decision making, 2023-07, Vol.23 (1), p.121-121, Article 121 [Peer Reviewed Journal]

2023. The Author(s). ;COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2023 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-023-02190-8 ;PMID: 37452338

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20
Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM)
Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM)
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Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM)

BMC medical informatics and decision making, 2022-07, Vol.22 (1), p.1-183, Article 183 [Peer Reviewed Journal]

COPYRIGHT 2022 BioMed Central Ltd. ;2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-022-01923-5 ;PMID: 35840972

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