AIMC Topic: ROC Curve

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Confederated learning in healthcare: Training machine learning models using disconnected data separated by individual, data type and identity for Large-Scale health system Intelligence.

Journal of biomedical informatics Jul 22, 2022
BACKGROUND: A patient's health information is generally fragmented across silos because it follows how care is delivered: multiple providers in multiple settings. Though it is technically feasible to reunite data for analysis in a manner that underpi...
ROC Curve Intelligence Privacy Machine Learning Delivery of Health Care Humans
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External validation of a machine learning model to predict hemodynamic instability in intensive care unit.

Critical care (London, England) Jul 14, 2022
BACKGROUND: Early prediction model of hemodynamic instability has the potential to improve the critical care, whereas limited external validation on the generalizability. We aimed to independently validate the Hemodynamic Stability Index (HSI), a mul...
Hemodynamics ROC Curve Retrospective Studies Intensive Care Units Machine Learning Humans
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Development of a machine learning model for the prediction of the short-term mortality in patients in the intensive care unit.

Journal of critical care Jul 11, 2022
PURPOSE: The aim of this study was to develop and evaluate a machine learning model that predicts short-term mortality in the intensive care unit using the trends of four easy-to-collect vital signs.
Area Under Curve Vital Signs Intensive Care Units ROC Curve Humans Machine Learning
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Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data.

Sensors (Basel, Switzerland) Jul 11, 2022
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for...
Neural Networks, Computer ROC Curve Radiography Privacy Humans X-Rays
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Predicting the risk of dental implant loss using deep learning.

Journal of clinical periodontology Jul 9, 2022
AIM: To investigate the feasibility of predicting dental implant loss risk with deep learning (DL) based on preoperative cone-beam computed tomography.
Retrospective Studies Risk Factors Cone-Beam Computed Tomography Humans Dental Implants Deep Learning ROC Curve
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Prediction of postoperative cardiac events in multiple surgical cohorts using a multimodal and integrative decision support system.

Scientific reports Jul 5, 2022
Postoperative patients are at risk of life-threatening complications such as hemodynamic decompensation or arrhythmia. Automated detection of patients with such risks via a real-time clinical decision support system may provide opportunities for earl...
Electronic Health Records ROC Curve Humans Machine Learning Postoperative Period Decision Support Systems, Clinical
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Feasibility of deep learning for dental caries classification in bitewing radiographs based on the ICCMS™ radiographic scoring system.

Oral surgery, oral medicine, oral pathology and oral radiology Jul 2, 2022
OBJECTIVE: To evaluate the potential of deep learning models for categorization of dental caries in bitewing radiographs based on the International Caries Classification and Management System (ICCMS™) radiographic scoring system (RSS).
Radiography, Bitewing Feasibility Studies Humans Radiography Deep Learning Dental Caries ROC Curve
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A comparative study on deep learning models for text classification of unstructured medical notes with various levels of class imbalance.

BMC medical research methodology Jul 2, 2022
BACKGROUND: Discharge medical notes written by physicians contain important information about the health condition of patients. Many deep learning algorithms have been successfully applied to extract important information from unstructured medical no...
ROC Curve Neural Networks, Computer Artificial Intelligence Algorithms Deep Learning Humans
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Fully automated determination of the cervical vertebrae maturation stages using deep learning with directional filters.

PloS one Jul 1, 2022
INTRODUCTION: We aim to apply deep learning to achieve fully automated detection and classification of the Cervical Vertebrae Maturation (CVM) stages. We propose an innovative custom-designed deep Convolutional Neural Network (CNN) with a built-in se...
Deep Learning Neural Networks, Computer Cervical Vertebrae ROC Curve
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Electrocardiogram analysis of post-stroke elderly people using one-dimensional convolutional neural network model with gradient-weighted class activation mapping.

Artificial intelligence in medicine Jun 30, 2022
Stroke is the second leading cause of death globally after ischemic heart disease, also a risk factor of cardioembolic stroke. Thus, we postulate that heartbeats encapsulate vital signals related to stroke. With the rapid advancement of deep neural n...
Heart Rate ROC Curve Electrocardiography Humans Neural Networks, Computer Aged
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