AIMC Topic: Deep Learning

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A deep learning model (FociRad) for automated detection of γ-H2AX foci and radiation dose estimation.

Scientific reports
DNA double-strand breaks (DSBs) are the most lethal form of damage to cells from irradiation. γ-H2AX (phosphorylated form of H2AX histone variant) has become one of the most reliable and sensitive biomarkers of DNA DSBs. However, the γ-H2AX foci assa...

AF2Complex predicts direct physical interactions in multimeric proteins with deep learning.

Nature communications
Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the sam...

Current progress and open challenges for applying deep learning across the biosciences.

Nature communications
Deep Learning (DL) has recently enabled unprecedented advances in one of the grand challenges in computational biology: the half-century-old problem of protein structure prediction. In this paper we discuss recent advances, limitations, and future pe...

A two-stage deep learning architecture for radiographic staging of periodontal bone loss.

BMC oral health
BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, inconsistency, and low efficiency in imaging diagnosis. Deep learning network may be a solution to im...

Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis.

Physics in medicine and biology
4D-CBCT provides phase-resolved images valuable for radiomics analysis for outcome prediction throughout treatment courses. However, 4D-CBCT suffers from streak artifacts caused by under-sampling, which severely degrades the accuracy of radiomic feat...

Synergistically segmenting choroidal layer and vessel using deep learning for choroid structure analysis.

Physics in medicine and biology
. The choroid is the most vascularized structure in the human eye, whose layer structure and vessel distribution are both critical for the physiology of the retina, and disease pathogenesis of the eye. Although some works have used graph-based method...

Prior information-based high-resolution tomography image reconstruction from a single digitally reconstructed radiograph.

Physics in medicine and biology
Tomography images are essential for clinical diagnosis and trauma surgery, allowing doctors to understand the internal information of patients in more detail. Since the large amount of x-ray radiation from the continuous imaging during the process of...

Multi-Modal Classification for Human Breast Cancer Prognosis Prediction: Proposal of Deep-Learning Based Stacked Ensemble Model.

IEEE/ACM transactions on computational biology and bioinformatics
Breast Cancer is a highly aggressive type of cancer generally formed in the cells of the breast. Despite significant advances in the treatment of primary breast cancer in the last decade, there is a dire need to attempt of an accurate predictive mode...

A Deep Learning Model for RNA-Protein Binding Preference Prediction Based on Hierarchical LSTM and Attention Network.

IEEE/ACM transactions on computational biology and bioinformatics
Attention mechanism has the ability to find important information in the sequence. The regions of the RNA sequence that can bind to proteins are more important than those that cannot bind to proteins. Neither conventional methods nor deep learning-ba...

Artificial intelligence-based detection of atrial fibrillation from chest radiographs.

European radiology
OBJECTIVE: The purpose of this study was to develop an artificial intelligence (AI)-based model to detect features of atrial fibrillation (AF) on chest radiographs.