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There is considerable variability in patient-reported outcome measures (PROM) following surgery for lumbar disk herniation (LDH). Individualized prediction tools that are derived from center- or even surgeon-specific data could provide valuable insights for shared decision-making.
This article was published in the following journal.
Name: The spine journal : official journal of the North American Spine Society
Value-based and patient-specific care represent 2 critical areas of focus that have yet to be fully reconciled by today's bundled care model. Using a predictive naïve Bayesian model, the objectives o...
A new goal for medical informatics is to develop robust tools that integrate clinical data on a patient in order to estimate the risk of imminent adverse events. This new field of predictive analytics...
This work aims to develop a new framework of image quality assessment using deep learning based model observer (DL-MO) and to validate it in a low-contrast lesion detection task that involves CT image...
The field of natural language processing (NLP) has seen rapid advances in the past several years since the introduction of deep learning techniques. A variety of NLP tasks including syntactic parsing,...
Predictive analytics monitoring, the use of patient data to provide continuous risk estimation of deterioration, is a promising new application of big data analytical techniques to the care of individ...
The proposed study seeks to assess the performance of continuous biosensor data and machine learning analytics in assessment of health patient status in a pulmonary rehabilitation program....
CT-guided epidural steroid injection (ESI) thrives among interventional radiologists. Although X-ray fluoroscopy still remains as the gold standard to guide ESI, CT guidance has the merits...
The aim of the present study is to develop and evaluate a computer-based methods for automated and improved detectation and classification of different colorectal laesions, especially poly...
Preoperative anxiety is a common occurrence for many patients undergoing all types of surgery. Patients with a high level of anxiety before surgery have been shown to have numerous negativ...
The study aim is to determine whether simulation based learning would improve senior anesthesiology residents' patient care performance during the insertion and management of cerebrospinal...
In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.
Assessment of the quality and effectiveness of health care as measured and directly reported by the patient.
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.
Surgery is a technology consisting of a physical intervention on tissues. All forms of surgery are considered invasive procedures; so-called "noninvasive surgery" usually refers to an excision that does not penetrate the structure being exci...