Trust in AI is crucial for effective and responsible use in high-stakes sectors like healthcare and finance. One of the most commonly used techniques to mitigate mistrust in AI and even increase trust is the use of Explainable AI models, which enables human understanding of certain decisions made by …

Pregnancy can be challenging for women as they experience various physical, psychological, and social changes that can lead to stress and potential mental health concerns. Being neglected in the long-term, sustained stress can increase the likelihood of postpartum depression, which can have significant …

Emergency responders (ERs) work in dynamic, complex, and unpredictable environments. The integration of increasingly advanced sensor and artificial intelligence technology affects the work processes and decision-making of ERs and leads to new challenges regarding efficient and responsible human-AI cooperation. …

Artificial Intelligence systems are more and more being introduced into first response; however, this introduction needs to be done responsibly. While generic claims on what this entails already exist, more details are required to understand the exact nature of responsible application of AI within the …

The healthcare sector has been confronted with rapidly rising health care costs and a shortage of medical staff. At the same time, the field of Artificial Intelligence (AI) has emerged as a promising area of research, offering poten tial benefits for healthcare. Despite the potential of AI to support …

In this paper, we present a framework for developing a Learning Health System (LHS) to provide means to a computerized clinical decision support system for allied healthcare and/or nursing professionals. LHSs are well suited to transform healthcare systems in a mission-oriented approach, and is being …

Patients on general wards are at risk of complications, often associated with deviations in vital signs. Unfortunately, the currently used manual method of intermittently measuring vital signs is not optimal, potentially leading to late recognition and treatment of complications, and sometimes with serious …

Aiming for increased accessibility and adaptability, higher educational institutes are making their curricula more flexible, offering students more freedom to choose what courses they want to take. Making a well-informed choice out of many possible elective courses is difficult, because it requires the …

The prevention and diagnosis of frailty syndrome (FS) in cardiac patients requires innovative systems to support medical personnel, patient adherence, and self-care behavior. To do so, modern medicine uses a supervised machine learning approach (ML) to study the psychosocial domains of frailty in cardiac …

Background: Continuous monitoring of vital signs (CMVS) using wearable wireless sensors is increasingly available to patients in general wards and can improve outcomes and reduce nurse workload. To assess the potential impact of such systems, successful implementation is important. We developed a CMVS …