AIMC Topic: Quality of Health Care

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Extracting Healthcare Quality Information from Unstructured Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Healthcare quality research is a fundamental task that involves assessing treatment patterns and measuring the associated patient outcomes to identify potential areas for improving healthcare. While both qualitative and quantitative approaches are us...

Deep learning for healthcare applications based on physiological signals: A review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.20...

Scoping review on the use of socially assistive robot technology in elderly care.

BMJ open
OBJECTIVE: With an elderly population that is set to more than double by 2050 worldwide, there will be an increased demand for elderly care. This poses several impediments in the delivery of high-quality health and social care. Socially assistive rob...

The ResQu Index: A new instrument to appraise the quality of research on birth place.

PloS one
OBJECTIVE: Place of birth is a known determinant of health care outcomes, interventions and costs. Many studies have examined the maternal and perinatal outcomes when women plan to give birth in hospitals compared with births in birth centres or at h...

Service innovation through social robot engagement to improve dementia care quality.

Assistive technology : the official journal of RESNA
Assistive technologies, such as robots, have proven to be useful in a social context and to improve the quality of life for people with dementia (PwD). This study aims to show how the engagement between two social robots and PwD in Australian residen...

MILS in a general surgery unit: learning curve, indications, and limitations.

Updates in surgery
Minimally invasive liver surgery (MILS) is going to be a method with a wide diffusion even in general surgery units. Organization, learning curve effect, and the environment are crucial issues to evaluate before starting a program of minimally invasi...

Automatic evidence quality prediction to support evidence-based decision making.

Artificial intelligence in medicine
BACKGROUND: Evidence-based medicine practice requires practitioners to obtain the best available medical evidence, and appraise the quality of the evidence when making clinical decisions. Primarily due to the plethora of electronically available data...

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...

Harnessing Natural Language Processing to Assess Quality of End-of-Life Care for Children With Cancer.

JCO clinical cancer informatics
PURPOSE: Data on end-of-life care (EOLC) quality, assessed through evidence-based quality measures (QMs), are difficult to obtain. Natural language processing (NLP) enables efficient quality measurement and is not yet used for children with serious i...