Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating the Perceived Utility of an Artificial Intelligence-Powered Clinical Decision Support System for Depression Treatment Using a Simulation Centre
2
Zitationen
22
Autoren
2021
Jahr
Abstract
Abstract Aifred is a clinical decision support system (CDSS) that uses artificial intelligence to assist physicians in selecting treatments for major depressive disorder (MDD) by providing probabilities of remission for different treatment options based on patient characteristics. We evaluated the utility of the CDSS as perceived by physicians participating in simulated clinical interactions. Twenty psychiatry and family medicine staff and residents completed a study in which each physician had three 10-minute clinical interactions with standardized patients portraying mild, moderate, and severe episodes of MDD. During these scenarios, physicians were given access to the CDSS, which they could use in their treatment decisions. The perceived utility of the CDSS was assessed through self-report questionnaires, scenario observations, and interviews. 60% of physicians perceived the CDSS to be a useful tool in their treatment-selection process, with family physicians perceiving the greatest utility. Moreover, 50% of physicians would use the tool for all patients with depression, with an additional 35% noting they would reserve the tool for more severe or treatment-resistant patients. Furthermore, clinicians found the tool to be useful in discussing treatment options with patients. The efficacy of this CDSS and its potential to improve treatment outcomes must be further evaluated in clinical trials.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.200 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.051 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.416 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.410 Zit.
Autoren
- Myriam Tanguay-Sela
- David Benrimoh
- Christina Popescu
- Tamara Pérez
- Colleen Rollins
- Emily Snook
- Eryn Lundrigan
- Caitrin Armstrong
- Kelly Perlman
- Robert Fratila
- Joseph Mehltretter
- Sonia Israel
- Monique Champagne
- Jerome D. Williams
- Jade Simard
- Sagar V. Parikh
- Jordan F. Karp
- Katherine Heller
- Outi Mantere
- Liliana Gómez Cardona
- Gustavo Turecki
- Howard C. Margolese