AIMC Topic: Patient Safety

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Predictive modeling of structured electronic health records for adverse drug event detection.

BMC medical informatics and decision making
BACKGROUND: The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. Th...

Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.

Computers in biology and medicine
Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurological diseases, adherence to medication regimens can be assessed by observing movement patterns. Howeve...

The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stroke significantly affects thousands of individuals annually, leading to considerable physical impairment and functional disability. Gait is one of the most important activities of daily living affected in stroke survivors. Recent techn...

Understanding safety-critical interactions with a home medical device through Distributed Cognition.

Journal of biomedical informatics
As healthcare shifts from the hospital to the home, it is becoming increasingly important to understand how patients interact with home medical devices, to inform the safe and patient-friendly design of these devices. Distributed Cognition (DCog) has...

An Evaluation of Patient Safety Event Report Categories Using Unsupervised Topic Modeling.

Methods of information in medicine
OBJECTIVE: Patient safety event data repositories have the potential to dramatically improve safety if analyzed and leveraged appropriately. These safety event reports often consist of both structured data, such as general event type categories, and ...

Identifying predictive features in drug response using machine learning: opportunities and challenges.

Annual review of pharmacology and toxicology
This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction ...

Integrating cybersecurity into healthcare quality governance: a policy perspective on artificial intelligence risks in Australia.

Australian health review : a publication of the Australian Hospital Association
The integration of artificial intelligence (AI) into Australian healthcare promises to improve diagnostic accuracy, workflow efficiency, and personalised care, yet it also introduces critical cybersecurity vulnerabilities that threaten not only data ...

[The alliance of cybersecurity and artificial intelligence in digital healthcare: challenges and solutions from the EU CYLCOMED RWD project.].

Recenti progressi in medicina
The availability of health technologies has facilitated improvements in the quality of care, playing a vital role in both hospital environments and remote patient monitoring. However, the growing complexity of these technologies has also led to an in...