AIMC Topic: Deep Learning

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Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: Comparison with the conventional respiratory-triggered technique.

European journal of radiology
OBJECTIVES: To assess the image quality of conventional respiratory-triggered 3-dimentional (3D) magnetic resonance cholangiopancreatography (Resp-MRCP) and breath-hold 3D MRCP (BH-MRCP) with and without denoising procedure using deep learning-based ...

Deep learning-augmented radioluminescence imaging for radiotherapy dose verification.

Medical physics
PURPOSE: We developed a novel dose verification method using a camera-based radioluminescence imaging system (CRIS) combined with a deep learning-based signal processing technique.

DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment.

PLoS computational biology
Drug treatment induces cell type specific transcriptional programs, and as the number of combinations of drugs and cell types grows, the cost for exhaustive screens measuring the transcriptional drug response becomes intractable. We developed DeepCel...

PM₂.₅ Monitoring: Use Information Abundance Measurement and Wide and Deep Learning.

IEEE transactions on neural networks and learning systems
This article devises a photograph-based monitoring model to estimate the real-time PM concentrations, overcoming currently popular electrochemical sensor-based PM monitoring methods' shortcomings such as low-density spatial distribution and time dela...

An Accurate Deep Learning Model for Clinical Entity Recognition From Clinical Notes.

IEEE journal of biomedical and health informatics
The growing use of electronic health records in the medical domain results in generating a large amount of medical data that is stored in the form of clinical notes. These clinical notes are enriched with clinical entities like disease, treatment, te...

WinBinVec: Cancer-Associated Protein-Protein Interaction Extraction and Identification of 20 Various Cancer Types and Metastasis Using Different Deep Learning Models.

IEEE journal of biomedical and health informatics
Biophysical protein-protein interactions perform dominant roles in the initiation and progression of many cancer-related pathways. A protein-protein interaction might play different roles in diverse cancer types. Hence, prioritizing the PPIs in each ...

A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images.

IEEE journal of biomedical and health informatics
Health professionals extensively use Two-Dimensional (2D) Ultrasound (US) videos and images to visualize and measure internal organs for various purposes including evaluation of muscle architectural changes. US images can be used to measure abdominal...

A Deep Learning Approach for Colonoscopy Pathology WSI Analysis: Accurate Segmentation and Classification.

IEEE journal of biomedical and health informatics
Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy pathology examination can identify cells of early-stage colon tumors in small tissue image slices. But, such examination is time-consuming and exhausting on high re...

Explainable Uncertainty-Aware Convolutional Recurrent Neural Network for Irregular Medical Time Series.

IEEE transactions on neural networks and learning systems
Influenced by the dynamic changes in the severity of illness, patients usually take examinations in hospitals irregularly, producing a large volume of irregular medical time-series data. Performing diagnosis prediction from the irregular medical time...

Class-Variant Margin Normalized Softmax Loss for Deep Face Recognition.

IEEE transactions on neural networks and learning systems
In deep face recognition, the commonly used softmax loss and its newly proposed variations are not yet sufficiently effective to handle the class imbalance and softmax saturation issues during the training process while extracting discriminative feat...