[Faster diagnosis of rare diseases with artificial intelligence-A precept of ethics, economy and quality of life].

作者信息

Völkel Lukas, Wagner Annette D

机构信息

Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Deutschland.

Abteilung für Nieren- und Hochdruckerkrankungen, Ambulanz für seltene entzündliche Systemerkrankungen mit Nierenbeteiligung, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Deutschland.

出版信息

Inn Med (Heidelb). 2023 Nov;64(11):1033-1040. doi: 10.1007/s00108-023-01599-7. Epub 2023 Oct 20.

Abstract

BACKGROUND

Approximately 300 million people worldwide suffer from a rare disease. An optimal treatment requires a successful diagnosis. This takes a particularly long time, especially for rare diseases. Digital diagnosis support systems could be important aids in accelerating a successful diagnosis in the future.

OBJECTIVE

The current possibilities of digital diagnostic support systems in the diagnosis of rare diseases and questions that still need to be clarified are presented in relation to the parameters of ethics, economy and quality of life.

MATERIAL AND METHODS

Current research results of the authors were compiled and discussed in the context of the current literature. A case study is used to illustrate the potential of digital diagnostic support systems.

RESULTS

Digital diagnostic support systems and experts together can accelerate the successful diagnosis in patients with rare diseases. This could have a positive impact on patients' quality of life and lead to potential savings in direct and indirect costs in the healthcare system.

CONCLUSION

Ensuring data security, legal certainty and functionality in the use of digital diagnostic support systems is of great importance in order to create trust among experts and patients. Continuous further development of the systems by means of artificial intelligence (AI) could also enable patients to accelerate diagnosis in the future.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f11/10602953/3a68c063c8a3/108_2023_1599_Fig1_HTML.jpg

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