Psoriasis

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

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 effectively analyze well-characterized data sets.

Smart identification of psoriasis by images using convolutional neural networks: a case study in China.

BACKGROUND: Psoriasis is a chronic inflammatory skin disease, which holds a high incidence in China. However, professional dermatologists who can diagnose psoriasis early and correctly are insufficient in China, especially in the rural areas. A smart approach to identify psoriasis by pictures would be highly adaptable countrywide and could play a useful role in early diagnosis and regular treatmen...

Coupled artificial neural networks to estimate 3D whole-body posture, lumbosacral moments, and spinal loads during load-handling activities.

Biomechanical modeling approaches require body posture to evaluate the risk of spine injury during manual material handling. The procedure to measure ...

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.

Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground rea...

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs.

BACKGROUND: Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related ...

Compositionally-warped Gaussian processes.

The Gaussian process (GP) is a nonparametric prior distribution over functions indexed by time, space, or other high-dimensional index set. The GP is ...

Classification of Skin Disease using Ensemble Data Mining Techniques.

Objective: Skin diseases are a major global health problem associated with high number of people. With the rapid development of technologies and the a...

Data augmentation in dermatology image recognition using machine learning.

BACKGROUND: Each year in the United States, over 80 million people are affected by acne, atopic dermatitis, rosacea, psoriasis, and impetigo. Artifici...

Intelligent inverse treatment planning via deep reinforcement learning, a proof-of-principle study in high dose-rate brachytherapy for cervical cancer.

Inverse treatment planning in radiation therapy is formulated as solving optimization problems. The objective function and constraints consist of mult...

Recomputation of the Dense Layers for Performance Improvement of DCNN.

Gradient descent optimization of learning has become a paradigm for training deep convolutional neural networks (DCNN). However, utilizing other learn...

Subrecursive neural networks.

It has been known for discrete-time recurrent neural networks (NNs) that binary-state models using the Heaviside activation function (with Boolean out...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, stro...

Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units.

BACKGROUND: Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in health care domains. To...

IVS2vec: A tool of Inverse Virtual Screening based on word2vec and deep learning techniques.

Inverse Virtual Screening is a powerful technique in the early stage of drug discovery process. This technique can provide important clues for biologi...

Estimation of constitutive parameters of the aortic wall using a machine learning approach.

The patient-specific biomechanical analysis of the aorta requires the quantification of the mechanical properties of individual patients. Current inv...

Serum Procalcitonin and Presepsin Levels in Patients with Generalized Pustular Psoriasis.

Patients with generalized pustular psoriasis (GPP) often present with symptoms that must be differentiated from sepsis. Procalcitonin (PCT) and presep...

Multi-Objective Genetic Algorithm Assisted by an Artificial Neural Network Metamodel for Shape Optimization of a Centrifugal Blood Pump.

A centrifugal blood pump is a common type of the pump used as a left ventricular assist device (LVAD) in the medical industries. The reduction of the ...

A neural microcircuit model for a scalable scale-invariant representation of time.

Scale-invariant timing has been observed in a wide range of behavioral experiments. The firing properties of recently described time cells provide a p...

Data-Driven Elasticity Imaging Using Cartesian Neural Network Constitutive Models and the Autoprogressive Method.

Quasi-static elasticity imaging techniques rely on model-based mathematical inverse methods to estimate mechanical parameters from force-displacement ...

Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is ...