AIMC Topic: Deep Learning

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Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Advances in experimental medicine and biology
Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into...

Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A Review.

Current medical imaging
BACKGROUND: This paper provides a systematic review of the application of Artificial Intelligence (AI) in the form of Machine Learning (ML) and Deep Learning (DL) techniques in fighting against the effects of novel coronavirus disease (COVID-19).

Deep Learning for Protein-Protein Interaction Site Prediction.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions (PPIs) are central to cellular functions. Experimental methods for predicting PPIs are well developed but are time and resource expensive and suffer from high false-positive error rates at scale. Computational prediction ...

Machine and Deep Learning for Prediction of Subcellular Localization.

Methods in molecular biology (Clifton, N.J.)
Protein subcellular localization prediction (PSLP), which plays an important role in the field of computational biology, identifies the position and function of proteins in cells without expensive cost and laborious effort. In the past few decades, v...

Applications of deep learning to the assessment of red blood cell deformability.

Biorheology
BACKGROUND: Measurement of abnormal Red Blood Cell (RBC) deformability is a main indicator of Sickle Cell Anemia (SCA) and requires standardized quantification methods. Ektacytometry is commonly used to estimate the fraction of Sickled Cells (SCs) by...

Deep learning assistance for tuberculosis diagnosis with chest radiography in low-resource settings.

Journal of X-ray science and technology
Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous researches of artificial intelligence (AI) have been conducted targeting at TB to reduce the diagnostic burden. However, most researches are conducted...

Deep Learning Models for Gastric Signet Ring Cell Carcinoma Classification in Whole Slide Images.

Technology in cancer research & treatment
Signet ring cell carcinoma (SRCC) of the stomach is a rare type of cancer with a slowly rising incidence. It tends to be more difficult to detect by pathologists, mainly due to its cellular morphology and diffuse invasion manner, and it has poor prog...

[Accuracy of Classification of Cerebral Blood Flow Reduction Patterns Using Statistical Analysis Images Generated with Simulated SPECT Datasets via Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: The aim of this study was to evaluate the classification accuracy of specific blood flow reduction patterns in clinical images by deep learning using simulation data.

The Application and Development of Deep Learning in Radiotherapy: A Systematic Review.

Technology in cancer research & treatment
With the massive use of computers, the growth and explosion of data has greatly promoted the development of artificial intelligence (AI). The rise of deep learning (DL) algorithms, such as convolutional neural networks (CNN), has provided radiation o...

Comparison of deep learning-based methods in multimodal anomaly detection: A case study in human-robot collaboration.

Science progress
Human-Robot Collaboration (HRC) has been widely used in daily life and industry for maximizing the advantages of humans and robots, respectively. However, the internal modeling errors or external perturbations still affect robotic systems such as hum...