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ALBERT-Based Self-Ensemble Model With Semisupervised Learning and Data Augmentation for Clinical Semantic Textual Similarity Calculation: Algorithm Validation Study

ALBERT-Based Self-Ensemble Model With Semisupervised Learning and Data Augmentation for Clinical Semantic Textual Similarity Calculation: Algorithm Validation Study

With major breakthroughs in the research of related algorithms in natural language processing and artificial intelligence, increasingly, research has been devoted to text information processing.Textual similarity calculation [1] is a key technology for efficient

Junyi Li, Xuejie Zhang, Xiaobing Zhou

JMIR Med Inform 2021;9(1):e23086


Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers

Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers

Recent research demonstrates the possibility to apply natural language processing (NLP) on electronic medical records to identify postoperative complications [9].

Adel Elmessiry, William O Cooper, Thomas F Catron, Jan Karrass, Zhe Zhang, Munindar P Singh

JMIR Med Inform 2017;5(3):e19


An Ensemble Learning Strategy for Eligibility Criteria Text Classification for Clinical Trial Recruitment: Algorithm Development and Validation

An Ensemble Learning Strategy for Eligibility Criteria Text Classification for Clinical Trial Recruitment: Algorithm Development and Validation

Using natural language processing and machine learning methods to automatically analyze clinical trial eligibility criteria texts and build an automated patient screening system is a promising research topic, with great practical application prospects and clinical

Kun Zeng, Zhiwei Pan, Yibin Xu, Yingying Qu

JMIR Med Inform 2020;8(7):e17832


The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance

The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance

To fill this gap, we sought to develop and test a natural language processing (NLP) method that would improve classification of OM among paramedic trip reports with documentation of naloxone administration or evidence of heroin use.MethodsSettingDenver Health

José Tomás Prieto, Kenneth Scott, Dean McEwen, Laura J Podewils, Alia Al-Tayyib, James Robinson, David Edwards, Seth Foldy, Judith C Shlay, Arthur J Davidson

J Med Internet Res 2020;22(1):e15645


Implementation of a Cohort Retrieval System for Clinical Data Repositories Using the Observational Medical Outcomes Partnership Common Data Model: Proof-of-Concept System Validation

Implementation of a Cohort Retrieval System for Clinical Data Repositories Using the Observational Medical Outcomes Partnership Common Data Model: Proof-of-Concept System Validation

The combination of natural language processing and information retrieval is a promising solution for cohort retrieval from unstructured clinical text, and there are several review articles [5,20] about information retrieval or natural language processing techniques

Sijia Liu, Yanshan Wang, Andrew Wen, Liwei Wang, Na Hong, Feichen Shen, Steven Bedrick, William Hersh, Hongfang Liu

JMIR Med Inform 2020;8(10):e17376


Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

Development of natural language processing (NLP) methods is essential to automatically transform clinical text into structured clinical data that can be directly processed using machine learning algorithms.

Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T Dudley, Alberto Lavelli, Fabio Rinaldi, Venet Osmani

JMIR Med Inform 2019;7(2):e12239


Biomedical Informatics Techniques for Processing and Analyzing Web Blogs of Military Service Members

Biomedical Informatics Techniques for Processing and Analyzing Web Blogs of Military Service Members

language processing (NLP) are commonly used to unlock information contained in free narrative-style text notes [2-4].

Sergiy Konovalov, Matthew Scotch, Lori Post, Cynthia Brandt

J Med Internet Res 2010;12(4):e45


Patient Triage by Topic Modeling of Referral Letters: Feasibility Study

Patient Triage by Topic Modeling of Referral Letters: Feasibility Study

Within the context of musculoskeletal conditions, natural language processing (NLP) was used successfully to automate the analysis of radiology reports [5,6] and patient questionnaires [7].Indeed, NLP has repeatedly demonstrated its feasibility to extract clinical

Irena Spasic, Kate Button

JMIR Med Inform 2020;8(11):e21252


Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

For example, micro-blogging (eg, Twitter) has been used to improve natural disaster and emergency response situations [5], and patient-generated data on the PatientsLikeMe website has been used to evaluate the effectiveness of a drug [6].

Albert Park, Andrea L Hartzler, Jina Huh, David W McDonald, Wanda Pratt

J Med Internet Res 2015;17(8):e212