{"title":"[头晕的鉴别诊断：人工智能的贡献是什么？］","authors":"Andreas Zwergal, Max Wuehr, Filipp Filippopulos","doi":"10.1055/a-2224-5894","DOIUrl":null,"url":null,"abstract":"<p><p>Dizziness is one of the most common reasons for medical consultations. The interdisciplinary range of differential diagnoses often leads to difficulties in proper classification. Artificial Intelligence and machine learning can assist through data-driven algorithms and facilitate the collection of important clinical signs as digital biomarkers. The article will present and critically discuss the current evidence on the topic.</p>","PeriodicalId":93975,"journal":{"name":"Deutsche medizinische Wochenschrift (1946)","volume":"149 23","pages":"1411-1419"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Differential diagnosis of dizziness: what's the contribution of Artificial Intelligence?]\",\"authors\":\"Andreas Zwergal, Max Wuehr, Filipp Filippopulos\",\"doi\":\"10.1055/a-2224-5894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Dizziness is one of the most common reasons for medical consultations. The interdisciplinary range of differential diagnoses often leads to difficulties in proper classification. Artificial Intelligence and machine learning can assist through data-driven algorithms and facilitate the collection of important clinical signs as digital biomarkers. The article will present and critically discuss the current evidence on the topic.</p>\",\"PeriodicalId\":93975,\"journal\":{\"name\":\"Deutsche medizinische Wochenschrift (1946)\",\"volume\":\"149 23\",\"pages\":\"1411-1419\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Deutsche medizinische Wochenschrift (1946)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1055/a-2224-5894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Deutsche medizinische Wochenschrift (1946)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1055/a-2224-5894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/6 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
[Differential diagnosis of dizziness: what's the contribution of Artificial Intelligence?]
Dizziness is one of the most common reasons for medical consultations. The interdisciplinary range of differential diagnoses often leads to difficulties in proper classification. Artificial Intelligence and machine learning can assist through data-driven algorithms and facilitate the collection of important clinical signs as digital biomarkers. The article will present and critically discuss the current evidence on the topic.
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