AIMC Topic: Patient Safety

Clear Filters Showing 151 to 160 of 202 articles

Making decisions: Bias in artificial intelligence and data‑driven diagnostic tools.

Australian journal of general practice
BACKGROUND: Although numerous studies have shown the potential of artificial intelligence (AI) systems in drastically improving clinical practice, there are concerns that these AI systems could replicate existing biases.

Scoping Review: Legal and Ethical Principles of Artificial Intelligence in Public Health.

Studies in health technology and informatics
The growing accessibility of large health datasets and AI's ability to analyze them offers significant potential to transform public health and epidemiology. AI-driven interventions in preventive, diagnostic, and therapeutic healthcare are becoming m...

A natural language processing approach to categorise contributing factors from patient safety event reports.

BMJ health & care informatics
OBJECTIVES: The objective of this study was to explore the use of natural language processing (NLP) algorithm to categorise contributing factors from patient safety event (PSE). Contributing factors are elements in the healthcare process (eg, communi...

Pressing issues in healthcare digital technologies and AI.

British journal of nursing (Mark Allen Publishing)
Lecturer in Law, Birmingham Law School, University of Birmingham, discusses several reports addressing patient safety, ethical and legal issues in healthcare digital technologies and artificial intelligence.

THE IMPACT OF THE INTRODUCTION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES ON THE CURRENT HUMAN RIGHTS AND FREEDOMS CONCEPT.

Polski merkuriusz lekarski : organ Polskiego Towarzystwa Lekarskiego
Artificial Intelligence (AI) has undeniably transformed the landscape of healthcare, offering unparalleled potential to enhance patient care, streamline diagnostics, and improve overall healthcare outcomes. As AI continues to make its way into the me...

Capturing and Improving Case Charge Accuracy in Robotic Surgery Programs.

Journal of the American College of Surgeons
The robotic platform offers many benefits to patients and surgeons; however, incorporating this new surgical tool has also introduced challenges in intraoperative documentation accuracy. In 2019, we began to investigate our institution's robotic intr...

Electronic surveillance of patient safety events using natural language processing.

Health informatics journal
OBJECTIVE: We describe our approach to surveillance of reportable safety events captured in hospital data including free-text clinical notes. We hypothesize that a) some patient safety events are documented only in the clinical notes and not in any o...

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward.

Journal of patient safety
Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of th...

A Machine Learning Approach to Reclassifying Miscellaneous Patient Safety Event Reports.

Journal of patient safety
BACKGROUND AND OBJECTIVES: Medical errors are a leading cause of death in the United States. Despite widespread adoption of patient safety reporting systems to address medical errors, making sense of the reports collected in these systems is challeng...