Algor-ethics: charting the ethical path for AI in critical care.
Jonathan MontomoliMaria Maddalena BitondoMarco CascellaEmanuele RezoagliLuca RomeoValentina BelliniFederico SemeraroEmiliano GamberiniEmanuele FrontoniVanni AgnolettiMattia AltiniPaolo BenantiElena Giovanna BignamiPublished in: Journal of clinical monitoring and computing (2024)
The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particularly in critical care, where physicians often deal with life-threating conditions requiring rapid actions and patients unable to participate in the decisional process. Moreover, development of AI-based CDSS is complex and should address different sources of bias, including data acquisition, health disparities, domain shifts during clinical use, and cognitive biases in decision-making. In this scenario algor-ethics is mandatory and emphasizes the integration of 'Human-in-the-Loop' and 'Algorithmic Stewardship' principles, and the benefits of advanced data engineering. The establishment of Clinical AI Departments (CAID) is necessary to lead AI innovation in healthcare, ensuring ethical integrity and human-centered development in this rapidly evolving field.
Keyphrases
- artificial intelligence
- big data
- healthcare
- machine learning
- deep learning
- endothelial cells
- clinical decision support
- public health
- electronic health record
- primary care
- end stage renal disease
- ejection fraction
- mental health
- newly diagnosed
- induced pluripotent stem cells
- prognostic factors
- transcription factor
- pluripotent stem cells
- drinking water
- global health
- human health
- risk assessment
- health information
- quality improvement
- sensitive detection