Julia Sellin, Jean Tori Pantel, Natalie Börsch, Rupert Conrad, Martin Mücke
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Despite initial positive evaluations, DDSS are not yet widely used, partly due to a lack of integration with existing clinical or practice information systems.</p><p><strong>Objective: </strong>This article provides an insight into currently existing diagnostic support systems that function without access to electronic patient records and only require information that is easily obtainable.</p><p><strong>Materials and methods: </strong>A systematic literature search identified eight articles on DDSS that can assist in the diagnosis of rare diseases with no need for access to electronic patient records or other information systems in practices and hospitals. The main advantages and disadvantages of the identified rare disease diagnostic support systems were extracted and summarized.</p><p><strong>Results: </strong>Symptom checkers and DDSS based on portrait photos and pain drawings already exist. The degree of maturity of these applications varies.</p><p><strong>Conclusion: </strong>DDSS currently still face a number of challenges, such as concerns about data protection and accuracy, and acceptance and awareness continue to be rather low. On the other hand, there is great potential for faster diagnosis, especially for rare diseases, which are easily overlooked due to their large number and the low awareness of them. The use of DDSS should therefore be carefully considered by doctors on a case-by-case basis.</p>","PeriodicalId":21572,"journal":{"name":"Schmerz","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Short paths to diagnosis with artificial intelligence: systematic literature review on diagnostic decision support systems].\",\"authors\":\"Julia Sellin, Jean Tori Pantel, Natalie Börsch, Rupert Conrad, Martin Mücke\",\"doi\":\"10.1007/s00482-023-00777-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Rare diseases are often recognized late. Their diagnosis is particularly challenging due to the diversity, complexity and heterogeneity of clinical symptoms. Computer-aided diagnostic aids, often referred to as diagnostic decision support systems (DDSS), are promising tools for shortening the time to diagnosis. Despite initial positive evaluations, DDSS are not yet widely used, partly due to a lack of integration with existing clinical or practice information systems.</p><p><strong>Objective: </strong>This article provides an insight into currently existing diagnostic support systems that function without access to electronic patient records and only require information that is easily obtainable.</p><p><strong>Materials and methods: </strong>A systematic literature search identified eight articles on DDSS that can assist in the diagnosis of rare diseases with no need for access to electronic patient records or other information systems in practices and hospitals. The main advantages and disadvantages of the identified rare disease diagnostic support systems were extracted and summarized.</p><p><strong>Results: </strong>Symptom checkers and DDSS based on portrait photos and pain drawings already exist. The degree of maturity of these applications varies.</p><p><strong>Conclusion: </strong>DDSS currently still face a number of challenges, such as concerns about data protection and accuracy, and acceptance and awareness continue to be rather low. On the other hand, there is great potential for faster diagnosis, especially for rare diseases, which are easily overlooked due to their large number and the low awareness of them. The use of DDSS should therefore be carefully considered by doctors on a case-by-case basis.</p>\",\"PeriodicalId\":21572,\"journal\":{\"name\":\"Schmerz\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Schmerz\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00482-023-00777-8\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/2 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ANESTHESIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Schmerz","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00482-023-00777-8","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/2 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
[Short paths to diagnosis with artificial intelligence: systematic literature review on diagnostic decision support systems].
Background: Rare diseases are often recognized late. Their diagnosis is particularly challenging due to the diversity, complexity and heterogeneity of clinical symptoms. Computer-aided diagnostic aids, often referred to as diagnostic decision support systems (DDSS), are promising tools for shortening the time to diagnosis. Despite initial positive evaluations, DDSS are not yet widely used, partly due to a lack of integration with existing clinical or practice information systems.
Objective: This article provides an insight into currently existing diagnostic support systems that function without access to electronic patient records and only require information that is easily obtainable.
Materials and methods: A systematic literature search identified eight articles on DDSS that can assist in the diagnosis of rare diseases with no need for access to electronic patient records or other information systems in practices and hospitals. The main advantages and disadvantages of the identified rare disease diagnostic support systems were extracted and summarized.
Results: Symptom checkers and DDSS based on portrait photos and pain drawings already exist. The degree of maturity of these applications varies.
Conclusion: DDSS currently still face a number of challenges, such as concerns about data protection and accuracy, and acceptance and awareness continue to be rather low. On the other hand, there is great potential for faster diagnosis, especially for rare diseases, which are easily overlooked due to their large number and the low awareness of them. The use of DDSS should therefore be carefully considered by doctors on a case-by-case basis.
期刊介绍:
Der Schmerz is an internationally recognized journal and addresses all scientists, practitioners and psychologists, dealing with the treatment of pain patients or working in pain research. The aim of the journal is to enhance the treatment of pain patients in the long run.
Review articles provide an overview on selected topics and offer the reader a summary of current findings from all fields of pain research, pain management and pain symptom management.
Freely submitted original papers allow the presentation of important clinical studies and serve the scientific exchange.
Case reports feature interesting cases and aim at optimizing diagnostic and therapeutic strategies.
Review articles under the rubric ''Continuing Medical Education'' present verified results of scientific research and their integration into daily practice.