AIMC Topic: Humans

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DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity.

Frontiers in immunology
Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen prediction focus on the binding between human leukocyte antigens (HLAs) and peptides, which is insufficient for high-confidence neoantigen prediction. In th...

Predicting atrial fibrillation in primary care using machine learning.

PloS one
BACKGROUND: Atrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of t...

A deep learning reconstruction framework for X-ray computed tomography with incomplete data.

PloS one
As a powerful imaging tool, X-ray computed tomography (CT) allows us to investigate the inner structures of specimens in a quantitative and nondestructive way. Limited by the implementation conditions, CT with incomplete projections happens quite oft...

Application of machine learning to determine top predictors of noncalcified coronary burden in psoriasis: An observational cohort study.

Journal of the American Academy of Dermatology
BACKGROUND: Psoriasis is associated with elevated risk of heart attack and increased accumulation of subclinical noncalcified coronary burden by coronary computed tomography angiography (CCTA). Machine learning algorithms have been shown to effective...

Systematic review of machine learning for diagnosis and prognosis in dermatology.

The Journal of dermatological treatment
Software systems using artificial intelligence for medical purposes have been developed in recent years. The success of deep neural networks (DNN) in 2012 in the image recognition challenge ImageNet LSVRC 2010 fueled expectations of the potential fo...

Machine Learning to Predict Acute Kidney Injury.

American journal of kidney diseases : the official journal of the National Kidney Foundation

Dysmorphology in a Genomic Era.

Clinics in perinatology
Dysmorphology is the practice of defining the morphologic phenotype of syndromic disorders. Genomic sequencing has advanced our understanding of human variation and molecular dysmorphology has evolved in response to the science of relating embryologi...

An optimal interval type-2 fuzzy logic control based closed-loop drug administration to regulate the mean arterial blood pressure.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The main aim of this work is to present an optimal and robust controller design in order to improve the drug infusion to the automatic control of mean arterial blood pressure in conditions like critically-ill or post-operati...

Deep learning, reusable and problem-based architectures for detection of consolidation on chest X-ray images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In most patients presenting with respiratory symptoms, the findings of chest radiography play a key role in the diagnosis, management, and follow-up of the disease. Consolidation is a common term in radiology, which indicate...

Deep Learning for Quantitative Cardiac MRI.

AJR. American journal of roentgenology
The recent advancement of deep learning techniques has profoundly impacted research on quantitative cardiac MRI analysis. The purpose of this article is to introduce the concept of deep learning, review its current applications on quantitative cardi...