Deep Learning Model Detecting Pressure Injury

Plain-language summary

In the health care system, pressure injuries, which are among the quality indicators, are a serious patient safety problem that affects the length of hospital stay and the cost of care. Pressure injuries are generally defined as localized injuries caused by pressure on bony prominences or by shear force combined with pressure. This health problem reduces the quality of life of the patient and their family, causes the individual to be socially isolated , requires more intensive and prolonged nursing care, and can cause mortality , morbidity and nosocomial infections if appropriate treatment and care are not provided . systematic staging of pressure injuries positively directs the treatment process and the patient's prognosis . Correct staging of pressure injuries not only affects patient care outcomes but also increases the quality of nursing care provided by providing a common language among nurses.Today, with the increasing use of technology, it is seen that larger data is needed to solve complex problems. In order to meet this need, Convolutional Neural Networks have emerged, which are used in many areas such as object recognition, speech recognition, and natural language processing, and can automatically learn from the symbols of data belonging to images, videos, audio, and texts, instead of learning with coded rules, unlike traditional machine learning methods, based on Artificial Neural Networks. Convolutional Neural Networks are one of the Deep Learning methods, which is a sub-branch of machine learning methods and has the ability to learn from examples. Convolutional Neural Networks are methods that can also learn from raw image or text data and whose prediction accuracy increases according to the size of the data. It has been proven in the literature that artificial intelligence and deep learning models are effective in the risk analysis of pressure injuries. However , no study has been found on the classification of pressure injuries. In light of this information, the study was conducted to develop a deep learning model in the detection and classification of pressure injuries and to determine the effect of the model on the knowledge and satisfaction levels of nurses.

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