Definition: A Diagnosis System is a digital service that uses artificial intelligence and machine learning algorithms to analyze patient data and provide potential diagnoses. It can be used in various medical fields, including radiology, pathology, dermatology, and more.
Source: Healthcare IT News
Source reference: https://www.healthcareitnews.com/news/ai-diagnosis-systems-are-coming-how-radiologists-can-stay-relevant
Additional information: A Diagnosis System is a sophisticated digital tool that helps healthcare professionals make more accurate and timely diagnoses. It uses AI and machine learning to analyze a wide range of patient data, including medical history, symptoms, test results, and imaging data. The system then uses this information to suggest potential diagnoses. This not only speeds up the diagnostic process but also helps to reduce the risk of human error. It's important to note that these systems are designed to support, not replace, healthcare professionals. They provide valuable insights and suggestions, but the final diagnosis is always made by a qualified healthcare professional.
Example: In radiology, a Diagnosis System can analyze imaging data to detect abnormalities that may indicate conditions such as cancer, fractures, or heart disease. It can also compare current images with previous ones to track the progression of a disease.
In dermatology, a Diagnosis System can analyze images of skin lesions and suggest whether they are likely to be benign or malignant. This can help dermatologists decide whether a biopsy is necessary.
In pathology, a Diagnosis System can analyze tissue samples to detect signs of diseases such as cancer. It can also help pathologists identify the type and stage of cancer, which is crucial for determining the most effective treatment.
LOST view: TVA-Health Patient Summary Enablers [Motivation]
Identifier: http://data.europa.eu/dr8/egovera/DiagnosisSystemApplicationService
EIRA traceability: eira:DigitalSolutionApplicationService
ABB name: egovera:DiagnosisSystemApplicationService
EIRA concept: eira:ArchitectureBuildingBlock
Last modification: 2023-08-04
dct:identifier: http://data.europa.eu/dr8/egovera/DiagnosisSystemApplicationService
dct:title: Diagnosis System Application Service
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eira:PURI | http://data.europa.eu/dr8/egovera/DiagnosisSystemApplicationService |
dct:modified | 2024-00-11 |
dct:identifier | http://data.europa.eu/dr8/egovera/DiagnosisSystemApplicationService |
dct:title | Diagnosis System Application Service |
dct:type | egovera:DiagnosisSystemApplicationService |
skos:definition | A Diagnosis System is a digital service that uses artificial intelligence and machine learning algorithms to analyze patient data and provide potential diagnoses. It can be used in various medical fields, including radiology, pathology, dermatology, and more. |
eira:definitionSource | Healthcare IT News |
eira:definitionSourceReference | https://www.healthcareitnews.com/news/ai-diagnosis-systems-are-coming-how-radiologists-can-stay-relevant |
skos:example | In radiology, a Diagnosis System can analyze imaging data to detect abnormalities that may indicate conditions such as cancer, fractures, or heart disease. It can also compare current images with previous ones to track the progression of a disease.
In dermatology, a Diagnosis System can analyze images of skin lesions and suggest whether they are likely to be benign or malignant. This can help dermatologists decide whether a biopsy is necessary.
In pathology, a Diagnosis System can analyze tissue samples to detect signs of diseases such as cancer. It can also help pathologists identify the type and stage of cancer, which is crucial for determining the most effective treatment. |
skos:note | A Diagnosis System is a sophisticated digital tool that helps healthcare professionals make more accurate and timely diagnoses. It uses AI and machine learning to analyze a wide range of patient data, including medical history, symptoms, test results, and imaging data. The system then uses this information to suggest potential diagnoses. This not only speeds up the diagnostic process but also helps to reduce the risk of human error. It's important to note that these systems are designed to support, not replace, healthcare professionals. They provide valuable insights and suggestions, but the final diagnosis is always made by a qualified healthcare professional. |
eira:concept | eira:ArchitectureBuildingBlock |
eira:view | TVA-Health Patient Summary Enablers [Motivation] |
eira:view | Technical view - application |
eira:businessDomain | health |
eira:eifLayer | TechnicalApplication |
skos:broader | http://data.europa.eu/dr8/DigitalSolutionApplicationService |