AIMC Topic: ROC Curve
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Detection of pre-mRNA involved in abnormal splicing using Graph Neural Network and Nearest Correlation Method.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
BACKGROUND: DNA is the building block of genetic information, and is composed of alternating sequences of exons with genetic information and introns without no genetic information. DNA is damaged by normal metabolic activities and environmental facto...
Enhancing sleep stage classification with 2-class stratification and permutation-based channel selection.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
We present a method that uses a convolutional neural network (CNN) called EEGNeX to extract and classify the characteristics of sleep-related waveforms from electroencephalographic (EEG) signals in different stages of sleep. Our results showed that t...
Noninvasive detection of diabetes in obstructive sleep apnea based on overnight SpO signal and deep learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The prevalence of obstructive sleep apnea comorbid with diabetes is high while the awareness of diabetes is low. There is a strong need for new diagnostic biomarkers to detect diabetes at an early stage. Therefore, we aimed to establish an automatic,...
Electrocardiographic Classification using Deep Learning with Lead Switching.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The classification algorithms of rhythm and morphology abnormalities in electrocardiogram (ECG) signals have been widely studied. However, the existing study uses ECGs with fixed leads. We propose a neural network-based method to improve the ECG clas...
Exploring Random Forest Machine Learning for Fetal Movement Detection using Abdominal Acceleration and Angular Rate Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Fetal movement is a commonly monitored indicator of fetal wellbeing with reductions in fetal movement being associated with poor perinatal outcomes. However, more informative datasets of fetal movement are required for improved clinical decision maki...
Cough Sound Based Deep Learning Models for Diagnosis of COVID-19 Using Statistical Features and Time-Frequency Spectrum.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This paper presents a deep learning model that can classify COVID-19 patients through cough sounds. The cough sound data were selected from the Cambridge data set which is a crowedsourced data set collected from the Cambridge COVID-19 sounds applicat...
EEG Tensorization Enhances CNN-Based Outcome Classification in Comatose Patients Following a Cardiac Arrest.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Standard diagnostic methods for evaluating the severity of brain injuries resulting from cardiac arrest, such as the Glasgow Coma Scale, exhibit subjective biases that lead to potentially fatal misclassifications, where life-support systems are prema...
Explainable Multimodal Deep Learning for Heart Sounds and Electrocardiogram Classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
We introduce a Gradient-weighted Class Activation Mapping (Grad-CAM) methodology to assess the performance of five distinct models for binary classification (normal/abnormal) of synchronized heart sounds and electrocardiograms. The applied models com...
SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance Scanning Laser Ophthalmoscopy Images.
Translational vision science & technology
Jul 1, 2024
PURPOSE: Several machine learning studies have used optical coherence tomography (OCT) for multiple sclerosis (MS) classification with promising outcomes. Infrared reflectance scanning laser ophthalmoscopy (IR-SLO) captures high-resolution fundus ima...
Implementation of a machine learning model in acute coronary syndrome and stroke risk assessment for patients with lower urinary tract symptoms.
Taiwanese journal of obstetrics & gynecology
Jul 1, 2024
OBJECTIVE: The global population is aging and the burden of lower urinary tract symptoms (LUTS) is expected to increase. According to the National Health Insurance Research Database, our previous studies have showed LUTS may predispose patients to ca...
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