AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 981 to 990 of 1118 articles

Organ Location Determination and Contour Sparse Representation for Multiorgan Segmentation.

IEEE journal of biomedical and health informatics
Organ segmentation on computed tomography (CT) images is of great importance in medical diagnoses and treatment. This paper proposes organ location determination and contour sparse representation methods (OLD-CSR) for multiorgan segmentation (liver, ...

A Deep Convolutional Neural Network-Based Framework for Automatic Fetal Facial Standard Plane Recognition.

IEEE journal of biomedical and health informatics
Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, conside...

Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports.

IEEE journal of biomedical and health informatics
Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this study, we investigated deep learning...

A Novel Continuous Blood Pressure Estimation Approach Based on Data Mining Techniques.

IEEE journal of biomedical and health informatics
Continuous blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for unobtrusive BP measurement. However, the accuracy of this approach must be improved for it to be viable for a wide range of applications. This study pr...

Early Detection of Peak Demand Days of Chronic Respiratory Diseases Emergency Department Visits Using Artificial Neural Networks.

IEEE journal of biomedical and health informatics
Chronic respiratory diseases, mainly asthma and chronic obstructive pulmonary disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) due to respiratory diseases...

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

IEEE journal of biomedical and health informatics
Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neu...

Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

IEEE journal of biomedical and health informatics
We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography. MRCNN employs Gabor-local binary pattern that introduces a good property in im...

A Natural Language Processing Framework for Assessing Hospital Readmissions for Patients With COPD.

IEEE journal of biomedical and health informatics
With the passage of recent federal legislation, many medical institutions are now responsible for reaching target hospital readmission rates. Chronic diseases account for many hospital readmissions and chronic obstructive pulmonary disease has been r...

A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare.

IEEE journal of biomedical and health informatics
Health analysis often involves prediction of multiple outcomes of mixed type. The existing work is restrictive to either a limited number or specific outcome types. We propose a framework for mixed-type multioutcome prediction. Our proposed framework...

Mobile Stride Length Estimation With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
OBJECTIVE: Accurate estimation of spatial gait characteristics is critical to assess motor impairments resulting from neurological or musculoskeletal disease. Currently, however, methodological constraints limit clinical applicability of state-of-the...