Latest AI and machine learning research in psoriasis for healthcare professionals.
Modern computational approaches and machine learning techniques accelerate the invention of new drugs. Generative models can discover novel molecular structures within hours, while conventional drug discovery pipelines require months of work. In this article, we propose a new generative architecture, entangled conditional adversarial autoencoder, that generates molecular structures based on variou...
Skin diseases have a serious impact on people's life and health. Current research proposes an efficient approach to identify singular type of skin diseases. It is necessary to develop automatic methods in order to increase the accuracy of diagnosis for multitype skin diseases. In this paper, three type skin diseases such as herpes, dermatitis, and psoriasis skin disease could be identified by a ne...
Recently, snake-like robots are proposed to assist experts during medical procedures on internal organs via natural orifices. Despite their well-spelt...
We introduce a model-based image reconstruction framework with a convolution neural network (CNN)-based regularization prior. The proposed formulation...
Accelerating the data acquisition of dynamic magnetic resonance imaging leads to a challenging ill-posed inverse problem, which has received great int...
Vitamin D deficiency in known to be high in obese and overweight adolescents. Few studies in other countries have shown lower parathyroid hormone (PTH...
Over the last few decades, medical-assisted robots have been considered by many researchers, within the research domain of robotics. In this article, ...
INTRODUCTION: The FDA Adverse Event Reporting System (FAERS) is a primary data source for identifying unlabeled adverse events (AEs) in a drug or biol...
The mathematical problem for electrical impedance tomography (EIT) is a highly nonlinear ill-posed inverse problem requiring carefully designed recons...
Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desirable ones has received much attention in recent ye...
The purpose of this study was to develop and train a Neural Network (NN) that uses barbell mass and motions to predict hip, knee, and ankle Net Joint ...
We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N bin...
BACKGROUND AND OBJECTIVE: Development of machine assisted tools for automatic analysis of psoriasis skin biopsy image plays an important role in clini...
Numerous studies have been focused on hydrophobic compounds encapsulation as oils. In fact, oils can provide numerous health benefits as synergic ingr...
Cesarean scar ectopic pregnancies and molar pregnancies are two very rare obstetric pathologies. In both cases, serious morbidities are involved that ...
The aim was to evaluate the role of klotho in the pathogenesis of systemic sclerosis (SSc), through the measurement of its serum concentration in SSc ...
Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information wher...
Identification of the original groundwater types present in geochemical mixtures observed in an aquifer is a challenging but very important task. Freq...
The purpose of this study was to determine the physical compatibility of micafungin with commonly used concentrations of sodium bicarbonate hydration...
Contrary to forward biomechanical functions, which are deterministic, inverse biomechanical functions are generally not. Calculating an inverse biomec...