AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 791 to 800 of 1118 articles

Accurate Deep Learning-Based Sleep Staging in a Clinical Population With Suspected Obstructive Sleep Apnea.

IEEE journal of biomedical and health informatics
The identification of sleep stages is essential in the diagnostics of sleep disorders, among which obstructive sleep apnea (OSA) is one of the most prevalent. However, manual scoring of sleep stages is time-consuming, subjective, and costly. To overc...

Automatic Identification of Breast Ultrasound Image Based on Supervised Block-Based Region Segmentation Algorithm and Features Combination Migration Deep Learning Model.

IEEE journal of biomedical and health informatics
Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial role in the successful treatment of the disease and the effective reduction of deaths. In this paper, deep learning technology combined with ultrasound imagin...

An Effective MR-Guided CT Network Training for Segmenting Prostate in CT Images.

IEEE journal of biomedical and health informatics
Segmentation of prostate in medical imaging data (e.g., CT, MRI, TRUS) is often considered as a critical yet challenging task for radiotherapy treatment. It is relatively easier to segment prostate from MR images than from CT images, due to better so...

Deep Learning Classification of Neuro-Emotional Phase Domain Complexity Levels Induced by Affective Video Film Clips.

IEEE journal of biomedical and health informatics
In the present article, a novel emotional complexity marker is proposed for classification of discrete emotions induced by affective video film clips. Principal Component Analysis (PCA) is applied to full-band specific phase space trajectory matrix (...

Mitral Annulus Segmentation Using Deep Learning in 3-D Transesophageal Echocardiography.

IEEE journal of biomedical and health informatics
3D Transesophageal Echocardiography is an excellent tool for evaluating the mitral valve and is also well suited for guiding cardiac interventions. We introduce a fully automatic method for mitral annulus segmentation in 3D Transesophageal Echocardio...

Deep Learning for Fall Risk Assessment With Inertial Sensors: Utilizing Domain Knowledge in Spatio-Temporal Gait Parameters.

IEEE journal of biomedical and health informatics
Fall risk assessment is essential to predict and prevent falls in geriatric populations, especially patients with life-long conditions like neurological disorders. Inertial sensor-based pervasive gait analysis systems have become viable means to faci...

Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics.

IEEE journal of biomedical and health informatics
OBJECTIVE: Histologic grade and Ki-67 proliferation status are important clinical indictors for breast cancer prognosis and treatment. The purpose of this study is to improve prediction accuracy of these clinical indicators based on tumor radiomic an...

Non-Invasive Estimation of Hemoglobin Using a Multi-Model Stacking Regressor.

IEEE journal of biomedical and health informatics
OBJECTIVE: We describe a novel machine-learning based method to estimate total Hemoglobin (Hb) using photoplethysmograms (PPGs) acquired non-invasively.

IoT-Enabled Dual-Arm Motion Capture and Mapping for Telerobotics in Home Care.

IEEE journal of biomedical and health informatics
With the paradigm shift from hospital-centric healthcare to home-centric healthcare in Healthcare 4.0, healthcare robotics has become one of the fastest growing fields of robotics. The combination of robot capabilities with human intelligence, for ex...

Early and Late Fusion Machine Learning on Multi-Frequency Electrical Impedance Data to Improve Radiofrequency Ablation Monitoring.

IEEE journal of biomedical and health informatics
Radiofrequency ablation (RFA) is a popular modality for tumor treatment. However, inexpensive real-time monitoring of RFA within multiple tissue types is still an ongoing research topic. The objective of this study is to utilize multi-frequency elect...