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Observation

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A doubly robust approach for cost-effectiveness estimation from observational data.

Statistical methods in medical research
Estimation of common cost-effectiveness measures, including the incremental cost-effectiveness ratio and the net monetary benefit, is complicated by the need to account for informative censoring and inherent skewness of the data. In addition, since t...

Accuracy of video observation and a three-dimensional head tracking system for detecting and quantifying robot-simulated head movements in cone beam computed tomography.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: To assess the accuracy of detecting robot-simulated head movements using video observation (VO) and 3-dimensional head tracking (HT) in a cone beam computed tomography examination setup.

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring treatment to the individual patient is essential for the best outcomes. In this paper, we t...

Structural, dynamical and symbolic observability: From dynamical systems to networks.

PloS one
Classical definitions of observability classify a system as either being observable or not. Observability has been recognized as an important feature to study complex networks, and as for dynamical systems the focus has been on determining conditions...

A symbolic network-based nonlinear theory for dynamical systems observability.

Scientific reports
When the state of the whole reaction network can be inferred by just measuring the dynamics of a limited set of nodes the system is said to be fully observable. However, as the number of all possible combinations of measured variables and time deriva...

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational heal...

Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations.

Evidence-based mental health
BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures pati...

Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research
BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this a...

A comparison of the fusion model of deep learning neural networks with human observation for lung nodule detection and classification.

The British journal of radiology
OBJECTIVES: To compare the diagnostic performance of a newly developed artificial intelligence (AI) algorithm derived from the fusion of convolution neural networks (CNN) versus human observers in the estimation of malignancy risk in pulmonary nodule...

Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Cause of death is used as an important outcome of clinical research; however, access to cause-of-death data is limited. This study aimed to develop and validate a machine-learning model that predicts the cause of death from the patient's l...