AIMC Topic: Patient Care Team

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Use of In-Situ Simulation Based Clinical Systems Test of Thoracic Robotic Surgery Emergencies.

The Journal of surgical research
INTRODUCTION: With the advancement of robotic surgery, some thoracic surgeons have been slow to adopt to this new operative approach, in part because they are un-scrubbed and away from the patient while operating. Aiming to allay surgeon concerns of ...

Artificial intelligence and multidisciplinary team meetings; a communication challenge for radiologists' sense of agency and position as spider in a web?

European journal of radiology
PURPOSE: This paper focuses on how the implementation of artificial intelligence algorithms (AI) challenges and changes the existing communication practice in radiology seen from a psychological communicative and clinical radiologist's perspective.

Simulation and beyond - Principles of effective obstetric training.

Best practice & research. Clinical obstetrics & gynaecology
Simulation training provides a safe, non-judgmental environment where members of the multi-professional team can practice both their technical and non-technical skills. Poor teamwork and communication are recurring contributing factors to adverse mat...

Augmenting the Transplant Team With Artificial Intelligence: Toward Meaningful AI Use in Solid Organ Transplant.

Frontiers in immunology
Advances in systems immunology, such as new biomarkers, offer the potential for highly personalized immunosuppression regimens that could improve patient outcomes. In the future, integrating all of this information with other patient history data wil...

Artificial Intelligence-Driven Oncology Clinical Decision Support System for Multidisciplinary Teams.

Sensors (Basel, Switzerland)
Watson for Oncology (WfO) is a clinical decision support system driven by artificial intelligence. In Korea, WfO is used by multidisciplinary teams (MDTs) caring for cancer patients. This study aimed to investigate the effect of WfO use on hospital s...

Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.

Breast (Edinburgh, Scotland)
Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and specialists over an extensive period of time. Communication is essential for treatment compliance, lowering error and complication risk, as well as handli...

Teaching cross-cultural design thinking for healthcare.

Breast (Edinburgh, Scotland)
OBJECTIVES: Artificial intelligence (AI) is poised to transform breast cancer care. However, most scientists, engineers, and clinicians are not prepared to contribute to the AI revolution in healthcare. In this paper, we describe our experiences teac...

Understanding health management and safety decisions using signal processing and machine learning.

BMC medical research methodology
BACKGROUND: Small group research in healthcare is important because it deals with interaction and decision-making processes that can help to identify and improve safer patient treatment and care. However, the number of studies is limited due to time-...