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View article: Application of a Natural Language Processing Algorithm to Early Asthma Ascertainment for Adults in the EHR Era
Application of a Natural Language Processing Algorithm to Early Asthma Ascertainment for Adults in the EHR Era Open
View article: Machine learning-based identification of natural history studies in rare diseases: a step toward understanding disease development and outcome
Machine learning-based identification of natural history studies in rare diseases: a step toward understanding disease development and outcome Open
According to the Food and Drug Administration’s definition, natural history studies (NHS) are observational studies that collect data on the course of a disease from onset to resolution or death, in the absence of an intervention. NHS play…
View article: 349 Rare Disease Alert System (RDAS) to promote rare disease research
349 Rare Disease Alert System (RDAS) to promote rare disease research Open
Objectives/Goals: Rare disease patients often face lengthy delays in receiving accurate diagnoses or experience misdiagnoses due to a lack of available information. The NCATS Rare Disease Alert System (RDAS) is a public, comprehensive rare…
View article: Length Representations in Large Language Models
Length Representations in Large Language Models Open
View article: Automated Identification of Patients’ Unmet Social Needs in Clinical Text Using Natural Language Processing
Automated Identification of Patients’ Unmet Social Needs in Clinical Text Using Natural Language Processing Open
View article: Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study
Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study Open
Background Extractive question-answering (EQA) is a useful natural language processing (NLP) application for answering patient-specific questions by locating answers in their clinical notes. Realistic clinical EQA can yield multiple answer…
View article: Acquisition of a Lexicon for Family History Information: Bidirectional Encoder Representations From Transformers–Assisted Sublanguage Analysis
Acquisition of a Lexicon for Family History Information: Bidirectional Encoder Representations From Transformers–Assisted Sublanguage Analysis Open
Background A patient’s family history (FH) information significantly influences downstream clinical care. Despite this importance, there is no standardized method to capture FH information in electronic health records and a substantial por…
View article: Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study
Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study Open
Background Aspirin-exacerbated respiratory disease (AERD) is an acquired inflammatory condition characterized by the presence of asthma, chronic rhinosinusitis with nasal polyposis, and respiratory hypersensitivity reactions on ingestion o…
View article: Acquisition of a Lexicon for Family History Information: Bidirectional Encoder Representations From Transformers–Assisted Sublanguage Analysis (Preprint)
Acquisition of a Lexicon for Family History Information: Bidirectional Encoder Representations From Transformers–Assisted Sublanguage Analysis (Preprint) Open
BACKGROUND A patient’s family history (FH) information significantly influences downstream clinical care. Despite this importance, there is no standardized method to capture FH information in electronic health records and a substantial po…
View article: Assessing document section heterogeneity across multiple electronic health record systems for computational phenotyping: A case study of heart-failure phenotyping algorithm
Assessing document section heterogeneity across multiple electronic health record systems for computational phenotyping: A case study of heart-failure phenotyping algorithm Open
Background The incorporation of information from clinical narratives is critical for computational phenotyping. The accurate interpretation of clinical terms highly depends on their associated context, especially the corresponding clinical…
View article: Contextual Variation of Clinical Notes induced by EHR Migration.
Contextual Variation of Clinical Notes induced by EHR Migration. Open
The structure and semantics of clinical notes vary considerably across different Electronic Health Record (EHR) systems, sites, and institutions. Such heterogeneity hampers the portability of natural language processing (NLP) models in ext…
View article: Digital Solutions Observed in Clinical Trials: A Formative Feasibility Scoping Review.
Digital Solutions Observed in Clinical Trials: A Formative Feasibility Scoping Review. Open
Growing digital access accelerates digital transformation of clinical trials where digital solutions (DSs) are increasingly and widely leveraged for improving trial efficiency, effectiveness, and accessibility. Many factors impact DS succe…
View article: Recommended practices and ethical considerations for natural language processing‐assisted observational research: A scoping review
Recommended practices and ethical considerations for natural language processing‐assisted observational research: A scoping review Open
An increasing number of studies have reported using natural language processing (NLP) to assist observational research by extracting clinical information from electronic health records (EHRs). Currently, no standardized reporting guideline…
View article: Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study (Preprint)
Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study (Preprint) Open
BACKGROUND Aspirin-exacerbated respiratory disease (AERD) is an acquired inflammatory condition characterized by the presence of asthma, chronic rhinosinusitis with nasal polyposis, and respiratory hypersensitivity reactions on ingestion …
View article: Quality assessment of functional status documentation in EHRs across different healthcare institutions
Quality assessment of functional status documentation in EHRs across different healthcare institutions Open
The secondary use of electronic health records (EHRs) faces challenges in the form of varying data quality-related issues. To address that, we retrospectively assessed the quality of functional status documentation in EHRs of persons parti…
View article: Rethinking blood eosinophil counts: Epidemiology, associated chronic diseases, and increased risks of cardiovascular disease
Rethinking blood eosinophil counts: Epidemiology, associated chronic diseases, and increased risks of cardiovascular disease Open
Blood eosinophil counts differ by demographic and clinical characteristics as well as by prevalent chronic disease. Moreover, elevated eosinophil counts are associated with risk of CVD. Further prospective investigations are needed to dete…
View article: Automated identification of aspirin exacerbated respiratory disease using natural language processing: a pilot study (Preprint)
Automated identification of aspirin exacerbated respiratory disease using natural language processing: a pilot study (Preprint) Open
BACKGROUND Aspirin exacerbated respiratory disease (AERD) is an acquired inflammatory condition characterized by the presence of asthma, chronic rhinosinusitis with nasal polyposis, and respiratory hypersensitivity reactions on ingestion …
View article: Development of a general purpose cognitive-behavioral symptom taxonomy
Development of a general purpose cognitive-behavioral symptom taxonomy Open
Motivation: Cognitive-behavior symptoms (CBSx) represent the surface manifestation of diverse etiology. Identification and documentation of CBSx are critical to biomedical research that targets understanding the association between the sym…
View article: Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study (Preprint)
Extractive Clinical Question-Answering With Multianswer and Multifocus Questions: Data Set Development and Evaluation Study (Preprint) Open
BACKGROUND Extractive question-answering (EQA) is a useful natural language processing (NLP) application for answering patient-specific questions by locating answers in their clinical notes. Realistic clinical EQA can yield multiple answe…
View article: A scoping review of medical practice variation research within the informatics literature
A scoping review of medical practice variation research within the informatics literature Open
View article: Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing
Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing Open
PURPOSE The advancement of natural language processing (NLP) has promoted the use of detailed textual data in electronic health records (EHRs) to support cancer research and to facilitate patient care. In this review, we aim to assess EHR …
View article: Computational drug repurposing based on electronic health records: a scoping review
Computational drug repurposing based on electronic health records: a scoping review Open
View article: Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification
Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification Open
Background Electronic health records (EHRs) are a rich source of longitudinal patient data. However, missing information due to clinical care that predated the implementation of EHR system(s) or care that occurred at different medical inst…
View article: Development of an Extractive Clinical Question Answering Dataset with Multi-Answer and Multi-Focus Questions
Development of an Extractive Clinical Question Answering Dataset with Multi-Answer and Multi-Focus Questions Open
Background: Extractive question-answering (EQA) is a useful natural language processing (NLP) application for answering patient-specific questions by locating answers in their clinical notes. Realistic clinical EQA can have multiple answer…
View article: Bridging the Granularity Gap in Family History Information Extracted from Clinical Narratives.
Bridging the Granularity Gap in Family History Information Extracted from Clinical Narratives. Open
Family history (FH) is important for disease risk assessment and prevention. However, incorporating FH information derived from electronic health records (EHRs) for downstream analytics is challenging due to the lack of standardization. We…
View article: Towards User-centered Corpus Development: Lessons Learnt from Designing and Developing MedTator.
Towards User-centered Corpus Development: Lessons Learnt from Designing and Developing MedTator. Open
A gold standard annotated corpus is usually indispensable when developing natural language processing (NLP) systems. Building a high-quality annotated corpus for clinical NLP requires considerable time and domain expertise during the annot…
View article: Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial
Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial Open
Rationale Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials. Objectives To assess the effective…
View article: Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population
Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population Open
Purpose The depth and breadth of clinical data within electronic health record (EHR) systems paired with innovative machine learning methods can be leveraged to identify novel risk factors for complex diseases. However, analysing the EHR i…
View article: Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification (Preprint)
Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification (Preprint) Open
BACKGROUND Electronic health records (EHRs) are a rich source of longitudinal patient data. However, missing information due to clinical care that predated the implementation of EHR system(s) or care that occurred at different medical ins…
View article: Clinical concept extraction: A methodology review
Clinical concept extraction: A methodology review Open