Latest AI and machine learning research in autism for healthcare professionals.
The speed and accuracy of phenotype detection from medical images are some of the most important qualities needed for any informed and timely response such as early detection of cancer or detection of desirable phenotypes for animal breeding. To improve both these qualities, the world is leveraging artificial intelligence and machine learning against this challenge. Most recently, deep learning ha...
Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) techniques can aid physicians to apply automatic diagnosis and rehabilitation procedures. AI techniques comprise traditional machine learning (ML) approaches and deep learning (DL) techniques. Conventional ML methods employ various...
Genetic mutations leading to the development of various diseases, such as cancer, diabetes, and neurodegenerative disorders, can be attributed to mult...
The genetic analysis of complex traits has been dominated by parametric statistical methods due to their theoretical properties, ease of use, computat...
A fit-for-purpose structural and statistical model is the first major requirement in population pharmacometric model development. In this manuscript w...
: Autism spectrum disorder (ASD) is a group of complex lifelong neurodevelopmental disorders, characterized by difficulties in social communication an...
BACKGROUND AND OBJECTIVE: Screening children for communicational disorders such as specific language impairment (SLI) is always challenging as it requ...
In order to explore the feasibility of applying neural network model to landscape planning, based on the multispecies evolutionary genetic algorithm, ...
BACKGROUND: Clinical interpretation of genetic variants in the context of the patient's phenotype is becoming the largest component of cost and time e...
Traditional symphony performances need to obtain a large amount of data in terms of effect evaluation to ensure the authenticity and stability of the ...
Approximately 4% of the world's population suffers from rare diseases. A vast majority of these disorders have a genetic background. The number of gen...
Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, whe...
The purpose of mobile robot path planning is to produce the optimal safe path. However, mobile robots have poor real-time obstacle avoidance in local ...
Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention that contributes to the early prevention and manageme...
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting geneticall...
A modular actuator construction consisting of smaller articulating units in series was designed to construct soft pneumatic actuators. These units are...
Background Patients who undergo surgery for cervical radiculopathy are at risk for developing adjacent segment disease (ASD). Identifying patients who...
Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet...
Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act t...
Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by ...