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Significant Risks and Responsibilities in the Clinical Use of AI Predictive Models. Comment on: “AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients”
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Significant Risks and Responsibilities in the Clinical Use of AI Predictive Models
Aymen Boud;
Ishraq Hussein
ABSTRACT
This letter responds to the article by Ruiz Giardin et al., titled “AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic.” Our letter raises important concerns regarding the clinical use of AI models, particularly Random Forest, focusing on the risk of overestimation, the implications of including AI outputs in patient records, and the potential impact on patient safety and confidentiality.
We briefly review the methodology and performance of the referenced model, and offer reflections on the need for clear guidelines and safeguards for implementation across different healthcare systems. Our aim is to contribute to ongoing discussions about responsible AI use in medicine.
Citation
Please cite as:
Boud A, Hussein I
Significant Risks and Responsibilities in the Clinical Use of AI Predictive Models. Comment on: “AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients”