AIMC Topic: Medical Errors

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A new deep learning model for assisted diagnosis on electrocardiogram.

Mathematical biosciences and engineering : MBE
In order to enhance the accuracy of computer aided electrocardiogram analysis, we propose a deep learning model called CBRNN to assist diagnosis on electrocardiogram for clinical medical service. It combines two sub networks which are convolutional n...

Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort...

Using Machine Learning-Based Multianalyte Delta Checks to Detect Wrong Blood in Tube Errors.

American journal of clinical pathology
OBJECTIVES: An unfortunate reality of laboratory medicine is that blood specimens collected from one patient occasionally get mislabeled with identifiers from a different patient, resulting in so-called "wrong blood in tube" (WBIT) errors and potenti...

Structuring Clinical Decision Support Rules for Drug Safety Using Natural Language Processing.

Studies in health technology and informatics
Drug safety is an important aspect in healthcare, resulting in a number of inadvertent events, which may harm the patients. IT based Clinical Decision Support (CDS), integrated in electronic-prescription or Electronic Health Records (EHR) systems, ca...

Automatic Analysis of Critical Incident Reports: Requirements and Use Cases.

Studies in health technology and informatics
Increasingly, critical incident reports are used as a means to increase patient safety and quality of care. The entire potential of these sources of experiential knowledge remains often unconsidered since retrieval and analysis is difficult and time-...

Enhancing Patient Safety Event Reporting by K-nearest Neighbor Classifier.

Studies in health technology and informatics
Data quality was placed as a major reason for the low utility of patient safety event reporting systems. A pressing need in improving data quality has advanced recent research focus in data entry associated with human factors. The debate on structure...

On Building an Ontological Knowledge Base for Managing Patient Safety Events.

Studies in health technology and informatics
Over the past decade, improving healthcare quality and safety through patient safety event reporting systems has drawn much attention. Unfortunately, such systems are suffering from low data quality, inefficient data entry and ineffective information...

Automated Classification of Clinical Incident Types.

Studies in health technology and informatics
We consider the task of automatic classification of clinical incident reports using machine learning methods. Our data consists of 5448 clinical incident reports collected from the Incident Information Management System used by 7 hospitals in the sta...

Toward a patient safety upper level ontology.

Studies in health technology and informatics
Patient Safety (PS) standardization is the key to improve interoperability and expand international share of incident reporting system knowledge. By aligning the Patient Safety Categorial Structure (PS-CAST) to the Basic Formal Ontology version 2 (BF...