deep learning

Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data 1978 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and… read more

Classification of IHC Images of NATs With ResNet-FRP-LSTM for Predicting Survival Rates of Rectal Cancer Patients
Classification of IHC Images of NATs With ResNet-FRP-LSTM for Predicting Survival Rates of Rectal Cancer Patients 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)
Background: Over a decade, tissues dissected adjacent to primary tumors have been considered “normal” or healthy samples (NATs). However, NATs have recently been discovered to be distinct from both tumorous… read more

Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI
Author(s)3: Seonyeong Park, H. Michael Gach, Siyong Kim, Suk Jin Lee, Yuichi Motai
Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Objective: To introduce an MRI in-plane resolution enhancement method that estimates High-Resolution (HR) MRIs from Low-Resolution (LR) MRIs. Method & Materials: Previous CNN-based MRI super-resolution methods cause loss of input…

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MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG
Author(s)3: Jing Zhang, Deng Liang, Aiping Liu, Min Gao, Xiang Chen, Xu Zhang, Xun Chenb
MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Automatic arrhythmia detection using 12-lead electrocardiogram (ECG) signal plays a critical role in early prevention and diagnosis of cardiovascular diseases. In the previous studies on automatic arrhythmia detection, most methods…

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A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data
Author(s)3: Md. Rashed-Al-Mahfuz, Mohammad Ali Moni, Shahadat Uddin, Salem A. Alyami, Mattew A. Summers, Valsamma Eapen
A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Background: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection…

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Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients using Primary Care Electronic Health Records
Author(s)3: Gavin Tsang, Shang-Ming Zhou, Xianghua Xie
Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients using Primary Care Electronic Health Records 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

A growing elderly population suffering from incurable, chronic conditions such as dementia present a continual strain on medical services due to mental impairment paired with high comorbidity resulting in increased…

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Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes

Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes
Author(s)3: Zeinab Golgooni, Sara Mirsadeghi, Mahdieh Soleymani Baghshah, Pedram Ataee, Hossein Baharvand, Sara Pahlavan, Hamid R. Rabiee
Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes 780 435 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

       Abstract: An early characterization of drug-induced cardiotoxicity may be possible by combining comprehensive in vitro proarrhythmia assay and deep learning techniques. We aimed to develop a method to automatically…

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