Sophie Huddart, Vijay Yadav, Solveig K Sieberts, Larson Omberg, Mihaja Raberahona, Rivo Rakotoarivelo, Issa N Lyimo, Omar Lweno, Devasahayam J Christopher, Nguyen Viet Nhung, Grant Theron, William Worodria, Charles Y Yu, Christine M Bachman, Stephen Burkot, Puneet Dewan, Sourabh Kulhare, Peter M Small, Adithya Cattamanchi, Devan Jaganath, Simon Grandjean Lapierre
{"title":"用于肺结核分诊测试的咳嗽声数据集。","authors":"Sophie Huddart, Vijay Yadav, Solveig K Sieberts, Larson Omberg, Mihaja Raberahona, Rivo Rakotoarivelo, Issa N Lyimo, Omar Lweno, Devasahayam J Christopher, Nguyen Viet Nhung, Grant Theron, William Worodria, Charles Y Yu, Christine M Bachman, Stephen Burkot, Puneet Dewan, Sourabh Kulhare, Peter M Small, Adithya Cattamanchi, Devan Jaganath, Simon Grandjean Lapierre","doi":"10.1038/s41597-024-03972-z","DOIUrl":null,"url":null,"abstract":"<p><p>Cough is a common and commonly ignored symptom of lung disease. Cough is often perceived as difficult to quantify, frequently self-limiting, and non-specific. However, cough has a central role in the clinical detection of many lung diseases including tuberculosis (TB), which remains the leading infectious disease killer worldwide. TB screening currently relies on self-reported cough which fails to meet the World Health Organization (WHO) accuracy targets for a TB triage test. Artificial intelligence (AI) models based on cough sound have been developed for several respiratory conditions, with limited work being done in TB. To support the development of an accurate, point-of-care cough-based triage tool for TB, we have compiled a large multi-country database of cough sounds from individuals being evaluated for TB. The dataset includes more than 700,000 cough sounds from 2,143 individuals with detailed demographic, clinical and microbiologic diagnostic information. We aim to empower researchers in the development of cough sound analysis models to improve TB diagnosis, where innovative approaches are critically needed to end this long-standing pandemic.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"11 1","pages":"1149"},"PeriodicalIF":5.8000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11489852/pdf/","citationCount":"0","resultStr":"{\"title\":\"A dataset of Solicited Cough Sound for Tuberculosis Triage Testing.\",\"authors\":\"Sophie Huddart, Vijay Yadav, Solveig K Sieberts, Larson Omberg, Mihaja Raberahona, Rivo Rakotoarivelo, Issa N Lyimo, Omar Lweno, Devasahayam J Christopher, Nguyen Viet Nhung, Grant Theron, William Worodria, Charles Y Yu, Christine M Bachman, Stephen Burkot, Puneet Dewan, Sourabh Kulhare, Peter M Small, Adithya Cattamanchi, Devan Jaganath, Simon Grandjean Lapierre\",\"doi\":\"10.1038/s41597-024-03972-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cough is a common and commonly ignored symptom of lung disease. Cough is often perceived as difficult to quantify, frequently self-limiting, and non-specific. However, cough has a central role in the clinical detection of many lung diseases including tuberculosis (TB), which remains the leading infectious disease killer worldwide. TB screening currently relies on self-reported cough which fails to meet the World Health Organization (WHO) accuracy targets for a TB triage test. Artificial intelligence (AI) models based on cough sound have been developed for several respiratory conditions, with limited work being done in TB. To support the development of an accurate, point-of-care cough-based triage tool for TB, we have compiled a large multi-country database of cough sounds from individuals being evaluated for TB. The dataset includes more than 700,000 cough sounds from 2,143 individuals with detailed demographic, clinical and microbiologic diagnostic information. We aim to empower researchers in the development of cough sound analysis models to improve TB diagnosis, where innovative approaches are critically needed to end this long-standing pandemic.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"11 1\",\"pages\":\"1149\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11489852/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-024-03972-z\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-03972-z","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
A dataset of Solicited Cough Sound for Tuberculosis Triage Testing.
Cough is a common and commonly ignored symptom of lung disease. Cough is often perceived as difficult to quantify, frequently self-limiting, and non-specific. However, cough has a central role in the clinical detection of many lung diseases including tuberculosis (TB), which remains the leading infectious disease killer worldwide. TB screening currently relies on self-reported cough which fails to meet the World Health Organization (WHO) accuracy targets for a TB triage test. Artificial intelligence (AI) models based on cough sound have been developed for several respiratory conditions, with limited work being done in TB. To support the development of an accurate, point-of-care cough-based triage tool for TB, we have compiled a large multi-country database of cough sounds from individuals being evaluated for TB. The dataset includes more than 700,000 cough sounds from 2,143 individuals with detailed demographic, clinical and microbiologic diagnostic information. We aim to empower researchers in the development of cough sound analysis models to improve TB diagnosis, where innovative approaches are critically needed to end this long-standing pandemic.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.