AIMC Topic: Hemorrhage

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Application of Deep Learning in Neuroradiology: Brain Haemorrhage Classification Using Transfer Learning.

Computational intelligence and neuroscience Jun 3, 2019
In this paper, we address the problem of identifying brain haemorrhage which is considered as a tedious task for radiologists, especially in the early stages of the haemorrhage. The problem is solved using a deep learning approach where a convolution...
Deep Learning Support Vector Machine Radiologists Hemorrhage Intracranial Hemorrhages Humans Neural Networks, Computer Machine Learning
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Total Knee Arthroplasty Is Safe and Successful in Patients With Klippel-Trénaunay Syndrome.

The Journal of arthroplasty Dec 22, 2018
BACKGROUND: Klippel-Trénaunay syndrome (KTS) is a severe vascular malformation that can lead to hypertrophic osteoarthritis. Total knee arthroplasty (TKA) performed in extremities affected with KTS is challenging given the high-risk vascular consider...
Adult Male Middle Aged Postoperative Period Blood Transfusion Humans Hemorrhage Klippel-Trenaunay-Weber Syndrome Knee Joint Female Tranexamic Acid Reoperation Aged Range of Motion, Articular Young Adult Arthroplasty, Replacement, Knee Tibia
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Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage.

Bioscience reports Dec 7, 2018
There is a disparity between the increasing application of digital retinal imaging to neonatal ocular screening and slowly growing number of pediatric ophthalmologists. Assistant tools that can automatically detect ocular disorders may be needed. In ...
Infant, Newborn Cross-Sectional Studies Image Processing, Computer-Assisted Fundus Oculi Retina Humans Neural Networks, Computer Hemorrhage Retinal Diseases
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Defining Massive Transfusion in Civilian Pediatric Trauma With Traumatic Brain Injury.

The Journal of surgical research Dec 4, 2018
The purpose of this study was to identify an optimal definition of massive transfusion in civilian pediatric trauma with severe traumatic brain injury (TBI) METHODS: Severely injured children (age ≤18 y) with severe TBI in the Trauma Quality Improvem...
Child Male Registries Blood Transfusion Humans Patient Selection Risk Assessment Brain Injuries, Traumatic Retrospective Studies Adolescent Survival Analysis Predictive Value of Tests Female Time Factors Hemorrhage Sensitivity and Specificity Child, Preschool Injury Severity Score
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Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.

PloS one Oct 19, 2018
Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with devastating adverse events. Remarkable efforts have been made to develop the machine learning based wa...
Thrombosis Hemorrhage Drug Administration Schedule Multivariate Analysis International Cooperation Polymorphism, Single Nucleotide Genotype Anticoagulants Warfarin Linkage Disequilibrium Medical Errors Vitamin K Epoxide Reductases Algorithms Databases, Factual Female Aged Aged, 80 and over Male Middle Aged Pharmacogenetics Cohort Studies Humans Machine Learning
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Using neural attention networks to detect adverse medical events from electronic health records.

Journal of biomedical informatics Oct 15, 2018
The detection of Adverse Medical Events (AMEs) plays an important role in disease management in ensuring efficient treatment delivery and quality improvement of health services. Recently, with the rapid development of hospital information systems, a ...
Myocardial Revascularization Hospital Information Systems Databases, Factual Electronic Health Records Cardiovascular Diseases Hospitals Humans Deep Learning China Neural Networks, Computer Area Under Curve Algorithms Hemorrhage Medical Informatics Myocardial Ischemia
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Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients.

JAMA network open Oct 5, 2018
IMPORTANCE: To improve patient safety, health care systems need reliable methods to detect adverse events in large patient populations. Events are often described in clinical notes, rather than structured data, which make them difficult to identify o...
Support Vector Machine Natural Language Processing Hemorrhage Aged, 80 and over Sensitivity and Specificity Critical Illness Male Humans Electronic Health Records Middle Aged Machine Learning Female ROC Curve Aged
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Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia.

PloS one Mar 29, 2018
Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variability of traditional vital signs, such as heart rate and blood pressure, and their inability to detect ...
Female Adult Male Case-Control Studies Photoplethysmography Humans Algorithms Hypovolemia Support Vector Machine Blood Volume Water-Electrolyte Imbalance Hemorrhage Wounds and Injuries
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Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.

Scientific reports Feb 24, 2017
The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide associ...
Erectile Dysfunction Radiation Tolerance Aged Gamma Rays Prostatic Neoplasms Biomarkers, Tumor Male Prostate Middle Aged Rectum Genome-Wide Association Study Hemorrhage Humans Cohort Studies Machine Learning Polymorphism, Single Nucleotide Prognosis Gene Expression Regulation, Neoplastic Signal Transduction Neoplasm Proteins
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Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
In blood transfusion studies, plasma transfusion (PPT) and bleeding are known to be associated with risk of prolonged ICU length of stay (ICU-LOS). However, as patients can show significant heterogeneity in response to a treatment, there might exists...
Humans Machine Learning Intensive Care Units Female Aged Aged, 80 and over Male Hemorrhage Risk Middle Aged Length of Stay Blood Transfusion Regression Analysis
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