AIMC Topic: Observation

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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 Jun 11, 2021
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...
Observation Middle Aged Deep Learning Imaging, Three-Dimensional Radiographic Image Interpretation, Computer-Assisted Iohexol Lung Neoplasms Contrast Media Aged Aged, 80 and over Adult Male Humans Tomography, X-Ray Computed Female
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Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
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...
Sepsis Infusions, Intravenous Fluid Therapy Observation Machine Learning Humans Intensive Care Units Vasoconstrictor Agents Deep Learning Retrospective Studies Medical History Taking
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Structural, dynamical and symbolic observability: From dynamical systems to networks.

PloS one Oct 31, 2018
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...
Observation Neural Networks, Computer Algorithms Models, Theoretical Nonlinear Dynamics
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A symbolic network-based nonlinear theory for dynamical systems observability.

Scientific reports Feb 28, 2018
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...
Algorithms Models, Theoretical Nonlinear Dynamics DNA Replication Humans Observation Neural Networks, Computer Systems Theory
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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 Feb 28, 2017
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.
Sensitivity and Specificity Cone-Beam Computed Tomography Imaging, Three-Dimensional Video Recording Observation Robotics Rotation Humans Manikins Head Movements
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A doubly robust approach for cost-effectiveness estimation from observational data.

Statistical methods in medical research Feb 27, 2017
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...
Diagnostic Tests, Routine Tomography, X-Ray Computed Observation Machine Learning Radiography, Thoracic Lung Neoplasms Propensity Score Algorithms Cost-Benefit Analysis Databases, Factual
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Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments.

Journal of evaluation in clinical practice Jul 15, 2016
RATIONALE, AIMS AND OBJECTIVES: Interventions with multivalued treatments are common in medical and health research; examples include comparing the efficacy of competing interventions and contrasting various doses of a drug. In recent years, there ha...
Humans Observation Aged Causality Regression Analysis Machine Learning Middle Aged Empirical Research Male Propensity Score Algorithms Treatment Outcome Female
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Inference of other's internal neural models from active observation.

Bio Systems Jan 21, 2015
Recently, there have been several attempts to replicate theory of mind, which explains how humans infer the mental states of other people using multiple sensory input, with artificial systems. One example of this is a robot that observes the behavior...
Observation Physics Theory of Mind Algorithms Computer Simulation Neural Networks, Computer Robotics Machine Learning Humans
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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 Jun 12, 2021
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...
Databases, Factual Prognosis Republic of Korea ROC Curve Humans Area Under Curve Machine Learning Cause of Death Decision Support Systems, Clinical Medical Records Systems, Computerized United States Observation Models, Statistical
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Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research Nov 1, 2020
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...
Reproducibility of Results Young Adult Adult Male Neural Networks, Computer Retrospective Studies Female Fractures, Closed Observation Scaphoid Bone Orthopedic Surgeons Middle Aged Deep Learning Radiography Humans
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