AIMC Topic: Deep Learning

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High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

European radiology
OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m,...

A multi-task two-path deep learning system for predicting the invasiveness of craniopharyngioma.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Craniopharyngioma is a kind of benign brain tumor in histography. However, it might be clinically aggressive and have severe manifestations, such as increased intracranial pressure, hypothalamic-pituitary dysfunction, and vi...

ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs.

Journal of computational biology : a journal of computational molecular cell biology
Template-based modeling (TBM), including homology modeling and protein threading, is one of the most reliable techniques for protein structure prediction. It predicts protein structure by building an alignment between the query sequence under predict...

Necessity of Local Modification for Deep Learning Algorithms to Predict Diabetic Retinopathy.

International journal of environmental research and public health
Deep learning (DL) algorithms are used to diagnose diabetic retinopathy (DR). However, most of these algorithms have been trained using global data or data from patients of a single region. Using different model architectures (e.g., Inception-v3, Res...

Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion.

Sensors (Basel, Switzerland)
After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for...

CNN Deep Learning with Wavelet Image Fusion of CCD RGB-IR and Depth-Grayscale Sensor Data for Hand Gesture Intention Recognition.

Sensors (Basel, Switzerland)
Pixel-based images captured by a charge-coupled device (CCD) with infrared (IR) LEDs around the image sensor are the well-known CCD Red-Green-Blue IR (the so-called CCD RGB-IR) data. The CCD RGB-IR data are generally acquired for video surveillance a...

A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.

Scientific reports
Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in the evaluation of well-being in individuals and the diagnosis and prognosis of hematologic diseases. For example, some blood disorders and immune system...

Optimization of College English Classroom Teaching Efficiency by Deep Learning SDD Algorithm.

Computational intelligence and neuroscience
In order to improve the teaching efficiency of English teachers in classroom teaching, the target detection algorithm in deep learning and the monitoring information from teachers are used, the target detection algorithm of deep learning Single Shot ...

Automated detection of COVID-19 through convolutional neural network using chest x-ray images.

PloS one
The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the...

DeLUCS: Deep learning for unsupervised clustering of DNA sequences.

PloS one
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of prim...