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Evaluating robustly standardized explainable anomaly detection of implausible variables in cancer data.
J Am Med Inform Assoc
January 2025
Information Systems and Business Administration, Johannes Gutenberg University, Mainz 55128, Germany.
Objectives: Explanations help to understand why anomaly detection algorithms identify data as anomalous. This study evaluates whether robustly standardized explanation scores correctly identify the implausible variables that make cancer data anomalous.
Materials And Methods: The dataset analyzed consists of 18 587 truncated real-world cancer registry records containing 8 categorical variables describing patients diagnosed with bladder and lung tumors.
Psychometric properties of the Mini-Balance Evaluation Systems Test (Mini-BESTest) among multiple populations: a COSMIN systematic review and meta-analysis.
Disabil Rehabil
January 2025
Department of Physiotherapy, University of Murcia, Murcia, Spain.
Purpose: To synthesize evidence regarding psychometric properties of the Mini-Balance Evaluation Systems Test (Mini-BESTest) in assessing postural control.
Method: Six databases were searched until October 15th, 2024. Two authors independently assessed the methodological quality and results of studies using the COSMIN checklist and Terweés criteria.
Effectiveness of room-of-error interventions for healthcare providers: a systematic review.
BMC Nurs
January 2025
College of Nursing, Research Institute of Nursing Science, Ajou University, 164 World cup-ro, Yeongtong-gu, Suwon, 16499, South Korea.
Background: Patient safety incidents are recognized as significant contributors to patient mortality, thus demanding immediate attention and strategic interventions in healthcare systems. The room-of-error education program serves as a solution, as it provides a case-based learning platform allowing nursing students to identify and resolve medical errors within a controlled environment systematically. This study aimed to identify the context, mechanisms, and outcomes of room-of-error training programs.
View Article and Find Full Text PDFCryogenic in-memory computing using magnetic topological insulators.
Nat Mater
January 2025
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
Machine learning algorithms have proven to be effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementation of these algorithms at cryogenic temperatures is essential. Here we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a cryogenic in-memory computing scheme based on the coexistence of a chiral edge state and a topological surface state.
View Article and Find Full Text PDFAvoiding never events in orthopaedics theatres: a quality improvement project.
BMJ Open Qual
January 2025
Trauma & Orthopaedics, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK.
Never events in the operating room are a surgeon's nightmare, with an incidence rate of 54%. These events are highly stressful for theatre staff and significantly compromise patient safety. The aim of this project is to avoid never events in trauma and orthopaedic theatres by ensuring that theatre staff adhere to the surgical pause and imaging pause protocols through regular audits.
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