Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI).
Int J Technol Assess Health Care
; 38(1): e74, 2022 Oct 03.
Article
en En
| MEDLINE
| ID: mdl-36189821
ABSTRACT
OBJECTIVES:
Artificial intelligence (AI) is seen as a major disrupting force in the future healthcare system. However, the assessment of the value of AI technologies is still unclear. Therefore, a multidisciplinary group of experts and patients developed a Model for ASsessing the value of AI (MAS-AI) in medical imaging. Medical imaging is chosen due to the maturity of AI in this area, ensuring a robust evidence-based model.METHODS:
MAS-AI was developed in three phases. First, a literature review of existing guides, evaluations, and assessments of the value of AI in the field of medical imaging. Next, we interviewed leading researchers in AI in Denmark. The third phase consisted of two workshops where decision makers, patient organizations, and researchers discussed crucial topics for evaluating AI. The multidisciplinary team revised the model between workshops according to comments.RESULTS:
The MAS-AI guideline consists of two steps covering nine domains and five process factors supporting the assessment. Step 1 contains a description of patients, how the AI model was developed, and initial ethical and legal considerations. In step 2, a multidisciplinary assessment of outcomes of the AI application is done for the five remaining domains safety, clinical aspects, economics, organizational aspects, and patient aspects.CONCLUSIONS:
We have developed an health technology assessment-based framework to support the introduction of AI technologies into healthcare in medical imaging. It is essential to ensure informed and valid decisions regarding the adoption of AI with a structured process and tool. MAS-AI can help support decision making and provide greater transparency for all parties.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Evaluación de la Tecnología Biomédica
/
Inteligencia Artificial
Tipo de estudio:
Diagnostic_studies
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Guideline
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Health_technology_assessment
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Prognostic_studies
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Qualitative_research
Límite:
Humans
Idioma:
En
Año:
2022
Tipo del documento:
Article