AIMC Topic: Deep Learning

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Deep learning in pharmacogenomics: from gene regulation to patient stratification.

Pharmacogenomics
This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepi...

An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images.

Scientific reports
Unlike daily routine images, ultrasound images are usually monochrome and low-resolution. In ultrasound images, the cancer regions are usually blurred, vague margin and irregular in shape. Moreover, the features of cancer region are very similar to n...

Single-shot T mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

Magnetic resonance in medicine
PURPOSE: An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T mapping from single-shot overlapping-echo detachment (OLED) planar imaging.

Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.

BMC systems biology
BACKGROUND: Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abd...

A deep learning approach for fetal QRS complex detection.

Physiological measurement
OBJECTIVE: Non-invasive foetal electrocardiography (NI-FECG) has the potential to provide more additional clinical information for detecting and diagnosing fetal diseases. We propose and demonstrate a deep learning approach for fetal QRS complex dete...

Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as...

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Deep learning based methods for retinal vessel segmentation are usually trained based on pixel-wise losses, which treat all vessel pixels with equal importance in pixel-to-pixel matching between a predicted probability map and the correspo...

Runners with patellofemoral pain demonstrate sub-groups of pelvic acceleration profiles using hierarchical cluster analysis: an exploratory cross-sectional study.

BMC musculoskeletal disorders
BACKGROUND: Previous studies have suggested that distinct and homogenous sub-groups of gait patterns exist among runners with patellofemoral pain (PFP), based on gait analysis. However, acquisition of 3D kinematic data using optical systems is time c...

Human Splice-Site Prediction with Deep Neural Networks.

Journal of computational biology : a journal of computational molecular cell biology
Accurate splice-site prediction is essential to delineate gene structures from sequence data. Several computational techniques have been applied to create a system to predict canonical splice sites. For classification tasks, deep neural networks (DNN...