AIMC Topic: Humans
Showing 64781 to 64790 of 95995 articles
Development and Validation of Machine Learning Models in Prediction of Remission in Patients With Moderate to Severe Crohn Disease.
JAMA network open
May 3, 2019
IMPORTANCE: Biological therapies have revolutionized inflammatory bowel disease management, but many patients do not respond to biological monotherapy. Identification of likely responders could reduce costs and delays in remission.
A Novel Internet of Things Framework Integrated with Real Time Monitoring for Intelligent Healthcare Environment.
Journal of medical systems
May 3, 2019
During mammogram screening, there is a higher probability that detection of cancers is missed, and more than 16 percentage of breast cancer is not detected by radiologists. This problem can be solved by employing image processing algorithms which enh...
Diagnostic ability of artificial intelligence using deep learning analysis of cyst fluid in differentiating malignant from benign pancreatic cystic lesions.
Scientific reports
May 3, 2019
The diagnosis of pancreatic cystic lesions remains challenging. This study aimed to investigate the diagnostic ability of carcinoembryonic antigen (CEA), cytology, and artificial intelligence (AI) by deep learning using cyst fluid in differentiating ...
Machine-learned target volume delineation of F-FDG PET images after one cycle of induction chemotherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
May 3, 2019
Biological tumour volume (GTV) delineation on F-FDG PET acquired during induction chemotherapy (ICT) is challenging due to the reduced metabolic uptake and volume of the GTV. Automatic segmentation algorithms applied to F-FDG PET (PET-AS) imaging hav...
Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine.
EBioMedicine
May 3, 2019
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating disease with high mortality rate. This study aimed to predict hematoma expansion in spontaneous ICH from routinely available variables by using support vector machine (SVM) metho...
Support Vector Machine
Cerebral Hemorrhage
Models, Biological
Hematoma
Odds Ratio
Glasgow Coma Scale
Male
Middle Aged
ROC Curve
Image Processing, Computer-Assisted
Young Adult
Adult
Sensitivity and Specificity
Humans
Biomarkers
Prognosis
Retrospective Studies
Tomography, X-Ray Computed
Female
Aged
Aged, 80 and over
Artificial Intelligence (AI) for the early detection of breast cancer: a scoping review to assess AI's potential in breast screening practice.
Expert review of medical devices
May 3, 2019
INTRODUCTION: Various factors are driving interest in the application of artificial intelligence (AI) for breast cancer (BC) detection, but it is unclear whether the evidence warrants large-scale use in population-based screening.
Defining Image Memorability Using the Visual Memory Schema.
IEEE transactions on pattern analysis and machine intelligence
May 2, 2019
Memorability of an image is a characteristic determined by the human observers' ability to remember images they have seen. Yet recent work on image memorability defines it as an intrinsic property that can be obtained independent of the observer. The...
Classification of Patients with Coronary Microvascular Dysfunction.
IEEE/ACM transactions on computational biology and bioinformatics
May 2, 2019
While coronary microvascular dysfunction (CMD) is a major cause of ischemia, it is very challenging to diagnose due to lack of CMD-specific screening measures. CMD has been identified as one of the five priority areas of investigation in a 2014 Natio...
Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.
Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
May 2, 2019
BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural network (DCNN) model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with cystic fibrosis (CF), performing similar...
Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI.
Journal of magnetic resonance imaging : JMRI
May 2, 2019
BACKGROUND: Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multisequence 3D imaging.
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