{"title":"结肠镜检查前肠道准备期间基于人工智能的粪便状态评估智能手机应用程序","authors":"Atsushi Inaba, Kensuke Shinmura, Hiroki Matsuzaki, Nobuyoshi Takeshita, Masashi Wakabayashi, Hironori Sunakawa, Keiichiro Nakajo, Tatsuro Murano, Tomohiro Kadota, Hiroaki Ikematsu, Tomonori Yano","doi":"10.1111/den.14827","DOIUrl":null,"url":null,"abstract":"<div>\n \n <section>\n \n <h3> Objectives</h3>\n \n <p>Colonoscopy (CS) is an important screening method for the early detection and removal of precancerous lesions. The stool state during bowel preparation (BP) should be properly evaluated to perform CS with sufficient quality. This study aimed to develop a smartphone application (app) with an artificial intelligence (AI) model for stool state evaluation during BP and to investigate whether the use of the app could maintain an adequate quality of CS.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>First, stool images were collected in our hospital to develop the AI model and were categorized into grade 1 (solid or muddy stools), grade 2 (cloudy watery stools), and grade 3 (clear watery stools). The AI model for stool state evaluation (grades 1–3) was constructed and internally verified using the cross-validation method. Second, a prospective study was conducted on the quality of CS using the app in our hospital. The primary end-point was the proportion of patients who achieved Boston Bowel Preparation Scale (BBPS) ≥6 among those who successfully used the app.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The AI model showed mean accuracy rates of 90.2%, 65.0%, and 89.3 for grades 1, 2, and 3, respectively. The prospective study enrolled 106 patients and revealed that 99.0% (95% confidence interval 95.3–99.9%) of patients achieved a BBPS ≥6.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>The proportion of patients with BBPS ≥6 during CS using the developed app exceeded the set expected value. This app could contribute to the performance of high-quality CS in clinical practice.</p>\n </section>\n </div>","PeriodicalId":159,"journal":{"name":"Digestive Endoscopy","volume":"36 12","pages":"1338-1346"},"PeriodicalIF":5.0000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smartphone application for artificial intelligence-based evaluation of stool state during bowel preparation before colonoscopy\",\"authors\":\"Atsushi Inaba, Kensuke Shinmura, Hiroki Matsuzaki, Nobuyoshi Takeshita, Masashi Wakabayashi, Hironori Sunakawa, Keiichiro Nakajo, Tatsuro Murano, Tomohiro Kadota, Hiroaki Ikematsu, Tomonori Yano\",\"doi\":\"10.1111/den.14827\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <section>\\n \\n <h3> Objectives</h3>\\n \\n <p>Colonoscopy (CS) is an important screening method for the early detection and removal of precancerous lesions. The stool state during bowel preparation (BP) should be properly evaluated to perform CS with sufficient quality. This study aimed to develop a smartphone application (app) with an artificial intelligence (AI) model for stool state evaluation during BP and to investigate whether the use of the app could maintain an adequate quality of CS.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>First, stool images were collected in our hospital to develop the AI model and were categorized into grade 1 (solid or muddy stools), grade 2 (cloudy watery stools), and grade 3 (clear watery stools). The AI model for stool state evaluation (grades 1–3) was constructed and internally verified using the cross-validation method. Second, a prospective study was conducted on the quality of CS using the app in our hospital. The primary end-point was the proportion of patients who achieved Boston Bowel Preparation Scale (BBPS) ≥6 among those who successfully used the app.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The AI model showed mean accuracy rates of 90.2%, 65.0%, and 89.3 for grades 1, 2, and 3, respectively. The prospective study enrolled 106 patients and revealed that 99.0% (95% confidence interval 95.3–99.9%) of patients achieved a BBPS ≥6.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>The proportion of patients with BBPS ≥6 during CS using the developed app exceeded the set expected value. This app could contribute to the performance of high-quality CS in clinical practice.</p>\\n </section>\\n </div>\",\"PeriodicalId\":159,\"journal\":{\"name\":\"Digestive Endoscopy\",\"volume\":\"36 12\",\"pages\":\"1338-1346\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digestive Endoscopy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/den.14827\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digestive Endoscopy","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/den.14827","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Smartphone application for artificial intelligence-based evaluation of stool state during bowel preparation before colonoscopy
Objectives
Colonoscopy (CS) is an important screening method for the early detection and removal of precancerous lesions. The stool state during bowel preparation (BP) should be properly evaluated to perform CS with sufficient quality. This study aimed to develop a smartphone application (app) with an artificial intelligence (AI) model for stool state evaluation during BP and to investigate whether the use of the app could maintain an adequate quality of CS.
Methods
First, stool images were collected in our hospital to develop the AI model and were categorized into grade 1 (solid or muddy stools), grade 2 (cloudy watery stools), and grade 3 (clear watery stools). The AI model for stool state evaluation (grades 1–3) was constructed and internally verified using the cross-validation method. Second, a prospective study was conducted on the quality of CS using the app in our hospital. The primary end-point was the proportion of patients who achieved Boston Bowel Preparation Scale (BBPS) ≥6 among those who successfully used the app.
Results
The AI model showed mean accuracy rates of 90.2%, 65.0%, and 89.3 for grades 1, 2, and 3, respectively. The prospective study enrolled 106 patients and revealed that 99.0% (95% confidence interval 95.3–99.9%) of patients achieved a BBPS ≥6.
Conclusion
The proportion of patients with BBPS ≥6 during CS using the developed app exceeded the set expected value. This app could contribute to the performance of high-quality CS in clinical practice.
期刊介绍:
Digestive Endoscopy (DEN) is the official journal of the Japan Gastroenterological Endoscopy Society, the Asian Pacific Society for Digestive Endoscopy and the World Endoscopy Organization. Digestive Endoscopy serves as a medium for presenting original articles that offer significant contributions to knowledge in the broad field of endoscopy. The Journal also includes Reviews, Original Articles, How I Do It, Case Reports (only of exceptional interest and novelty are accepted), Letters, Techniques and Images, abstracts and news items that may be of interest to endoscopists.