Topic modeling to characterize the natural history of ANCA-Associated vasculitis from clinical notes: A proof of concept study

Wang, Liqin; Miloslavsky, Eli M.; Stone, John H.; Choi, Hyon K.; Zhou, Li; Wallace, Zachary S

doi:10.1016/j.semarthrit.2020.10.012

Cited by 9 publications

(10 citation statements)

References 25 publications

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“…This suggests that automated topic modelling can perform this categorisation with similar accuracy to human annotators. Existing use of automated topic modelling techniques in clinical research is relatively uncommon and typically limited to latent dirichlet allocation (LDA)‐based topic modelling techniques 20,21 . This is an older, but better established, method that typically requires extensive text pre‐processing in comparison to the more recently developed BERTopic algorithm 19,22 .…”

Section: Discussionmentioning

confidence: 99%

“…Existing use of automated topic modelling techniques in clinical research is relatively uncommon and typically limited to latent dirichlet allocation (LDA)-based topic modelling techniques. 20,21 This is an older, but better established, method that typically requires extensive text pre-processing in comparison to the more recently developed BERTopic algorithm. 19,22 Few prior clinical research studies have sought to manually validate the categories assigned by automated topic models to each document.…”

Section: Discussionmentioning

confidence: 99%

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Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling

Williams

Luo

et al. 2023

Clinical Otolaryngology

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Objective: There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community. Materials and Methods: Cross-sectional study of posts on the online Reddit r/CochlearImplants forum from 1 March 2015 to 11 November 2021. Natural language processing using the BERTopic automated topic modelling technique was employed to cluster posts into semantically similar topics. Topic categorisation was manually validated by two independent reviewers and Cohen's kappa calculated to determine inter-rater reliability between machine vs human and human vs human categorisation. Results: We retrieved 987 posts from 588 unique Reddit users on the r/CochlearImplants forum. Posts were initially categorised by BERTopic into 16 different Topics, which were increased to 23 Topics following manual inspection. The most popular topics related to CI connectivity (n = 112), adults considering getting a CI (n = 107), surgery-related posts (n = 89) and day-to-day living with a CI (n = 85).Cohen's kappa among all posts was 0.62 (machine vs. human) and 0.72 (human vs. human), and among categorised posts was 0.85 (machine vs. human) and 0.84 (human vs. human). Conclusions:This cross-sectional study of social media discussions among the online cochlear implant community identified common attitudes, experiences and concerns of patients living with, or seeking, a cochlear implant. Our validation of natural language processing methods to categorise topics shows that automated analysis of similar Otolaryngology-related content is a viable and accurate alternative to manual qualitative approaches.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling

Williams

Luo

et al. 2023

Clinical Otolaryngology

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“…We included the ICD‐9 code for polyarteritis nodosa (446.0) because there is no specific ICD‐9 code for microscopic polyangiitis, and the polyarteritis nodosa code might have been used by some providers. Additionally, we linked patients with ESRD attributable to AAV in the MGB AAV cohort, a consecutive inception cohort of confirmed AAV cases in the MGB system ( 7 , 8 , 9 ), to their USRDS records, if possible, using the same methods.…”

Section: Methodsmentioning

confidence: 99%

Validation of Antineutrophil Cytoplasmic Antibody–Associated Vasculitis as the Cause of End‐Stage Renal Disease in the US Renal Data System

Cook

Zhang

et al. 2021

ACR Open Rheumatology

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Objective. The objective of this study was to validate the diagnosis of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) as the primary cause of end-stage renal disease (ESRD) in the US Renal Data System (USRDS).Methods. We identified patients with ESRD in the Mass General Brigham (MGB) health care system who were enrolled in the USRDS. The health records of those with AAV listed as the primary cause of ESRD in the USRDS were reviewed to confirm the diagnosis and estimate positive predictive value (PPV). Sensitivity was estimated by evaluating the primary cause of ESRD listed in the USRDS for patients with ESRD due to AAV in the MGB AAV cohort.Results. We identified 89 MGB patients with ESRD due to AAV in the USRDS. Of these, 85 cases were confirmed to be true cases of AAV (PPV = 94%). Among the patients classified as having AAV, 84 (99%) had an ANCA test, which was predominantly myeloperoxidase/P-ANCA (47 [55%]); 36 (42%) had a renal biopsy, and all biopsies were supportive of the diagnosis. The majority (81 [90%]) was identified as AAV by International Classification of Diseases Ninth Revision or International Classification of Diseases 10th Revision codes for granulomatosis with polyangiitis (446.4 or M313.1). Of the 77 MGB AAV cohort patients with ESRD who were linked to the USRDS, 41 (53%) had AAV listed as the cause of ESRD; in the remainder, ESRD was attributed to nonspecific nephritis.Conclusion. The diagnosis of AAV as the cause of ESRD in the USRDS has a high PPV; sensitivity was moderate. These findings support the continued use of the USRDS to study ESRD due to AAV.

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“…Topic modelling has been applied to characterise the temporal evolution of ANCA-Associated Vasculitis (AAV) in [6]. With a follow-up of seven years, more than 113,000 clinical notes from 660 patients were processed following a topic modelling approach.…”

Section: Disease Progression and Disease Activity 361 Clinical And De...mentioning

confidence: 99%

“…Although RWD has been shown to be a valuable source of information, some of its implications cannot be neglected, such as its less structured nature or the occurrence of biases (i.e., selection bias or informed consent bias) which may require additional processing [5]. In this regard, approaches based on Natural Language Processing (NLP) and topic modelling have been proposed to characterise the evolution of rare diseases in RMDs clinical narratives [6].…”

Section: Introductionmentioning

confidence: 99%

Understanding the role and adoption of artificial intelligence techniques in rheumatology research: an in-depth review of the literature

Madrid

Merino‐Barbancho

Rodríguez-González

et al. 2022

Preprint

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The outstanding and upward trend in the number of published research related to rheumatic and musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the interest of rheumatology researchers in using these techniques to answer their research questions. In this review, we analyse the original research articles that combine both worlds in a five-year period (2017-2021). In contrast to other published papers on the same topic, we first studied the review and recommendation articles that were published during that period, including up to October 2022, as well as the publication trends. Secondly, we review the published research articles and classify them into one of the following categories: disease classification, disease prediction, predictors identification, patient stratification and disease subtype identification, disease progression and activity, and treatment response. Thirdly, we provide a table with illustrative studies in which artificial intelligence techniques have played a central role in more than twenty rheumatic and musculoskeletal diseases. Finally, the findings of the research articles, in terms of disease and/or data science techniques employed are highlighted in a discussion. Therefore, the present review arises with the aim of characterising how researchers are employing data science techniques in the rheumatology medical field.

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Topic modeling to characterize the natural history of ANCA-Associated vasculitis from clinical notes: A proof of concept study

Cited by 9 publications

References 25 publications

Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling

Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling

Validation of Antineutrophil Cytoplasmic Antibody–Associated Vasculitis as the Cause of End‐Stage Renal Disease in the US Renal Data System

Understanding the role and adoption of artificial intelligence techniques in rheumatology research: an in-depth review of the literature

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