AIMC Topic: Pressure Ulcer

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Modeling and prediction of pressure injury in hospitalized patients using artificial intelligence.

BMC medical informatics and decision making
BACKGROUND: Hospital-acquired pressure injuries (PIs) induce significant patient suffering, inflate healthcare costs, and increase clinical co-morbidities. PIs are mostly due to bed-immobility, sensory impairment, bed positioning, and length of hospi...

Exploring a Fuzzy Rule Inferred ConvLSTM for Discovering and Adjusting the Optimal Posture of Patients with a Smart Medical Bed.

International journal of environmental research and public health
Several countries nowadays are facing a tough social challenge caused by the aging population. This public health issue continues to impose strain on clinical healthcare, such as the need to prevent terminal patients' pressure ulcers. Provocative app...

Supervised machine learning-based prediction for in-hospital pressure injury development using electronic health records: A retrospective observational cohort study in a university hospital in Japan.

International journal of nursing studies
BACKGROUND: In hospitals, nurses are responsible for pressure injury risk assessment using several kinds of risk assessment scales. However, their predictive validity is insufficient to initiate targeted preventive strategy for each patient. The use ...

Predicting the Development of Surgery-Related Pressure Injury Using a Machine Learning Algorithm Model.

The journal of nursing research : JNR
BACKGROUND: Surgery-related pressure injury (SRPI) is a serious problem in patients who undergo cardiovascular surgery. Identifying patients at a high risk of SRPI is important for clinicians to recognize and prevent it expeditiously. Machine learnin...

A model for predicting 7-day pressure injury outcomes in paediatric patients: A machine learning approach.

Journal of advanced nursing
AIMS: We sought to explore factors associated with early pressure injury progression and build a model for predicting these outcomes using a machine learning approach.

Automatic measurement of pressure ulcers using Support Vector Machines and GrabCut.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Pressure ulcers are regions of trauma caused by a continuous pressure applied to soft tissues between a bony prominence and a hard surface. The manual monitoring of their healing evolution can be achieved by area assessment ...

Integrating 3D Model Representation for an Accurate Non-Invasive Assessment of Pressure Injuries with Deep Learning.

Sensors (Basel, Switzerland)
Pressure injuries represent a major concern in many nations. These wounds result from prolonged pressure on the skin, which mainly occur among elderly and disabled patients. If retrieving quantitative information using invasive methods is the most us...

Pressure injury image analysis with machine learning techniques: A systematic review on previous and possible future methods.

Artificial intelligence in medicine
Pressure injuries represent a tremendous healthcare challenge in many nations. Elderly and disabled people are the most affected by this fast growing disease. Hence, an accurate diagnosis of pressure injuries is paramount for efficient treatment. The...

Artificial Neural Network for in-Bed Posture Classification Using Bed-Sheet Pressure Sensors.

IEEE journal of biomedical and health informatics
Pressure ulcer prevention is a vital procedure for patients undergoing long-term hospitalization. A human body lying posture (HBLP) monitoring system is essential to reschedule posture change for patients. Video surveillance, the conventional method ...

Pressure redistributing in-seat movement activities by persons with spinal cord injury over multiple epochs.

PloS one
Pressure ulcers, by definition, are caused by external forces on the tissues, often in the regions of bony prominences. Wheelchair users are at risk to develop sitting-acquired pressure ulcers, which occur in the regions of the ischial tuberosities, ...