Latest AI and machine learning research in autism for healthcare professionals.
Heavy metal pollution is a global ecological safety issue, especially in crops, where it directly threatens regional ecological security and human health. In this study, the back-propagation (BP) neural network optimized by the genetic algorithm (GA) was used to predict the concentration of cadmium (Cd) in rice grain based on influencing factors. As an intelligent information processing system, th...
Prediction of sediment volume and sediment load is always one of the important issues for decision-makers of watershed basins. The present study investigated the daily suspended sediment load in a watershed basin using the improved support vector machine method. Since in most of the previous studies, the coefficients of the support vector machine method had been calculated based on trial and error...
Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many pu...
Machine learning is becoming an increasingly popular approach for investigating spatially distributed and subtle neuroanatomical alterations in brain-...
We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin...
Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has attracted increasing attention, since a large num...
Near-infrared (NIR) spectral sensors deliver the spectral response of the light absorbed by materials for quantification, qualification or identificat...
Autism spectrum disorder is associated with significant healthcare costs, and early diagnosis can substantially reduce these. Unfortunately, waiting t...
Deep learning has become the new state-of-the-art for many problems in image analysis. However, large datasets are often required for such deep networ...
BACKGROUND: A growing body of anecdotal evidence indicates that the use of robots may provide unique opportunities for assisting children with autism ...
The genetic analysis of complex traits does not escape the current excitement around artificial intelligence, including a renewed interest in "deep le...
Autism Spectrum Disorder (ASD) affects approximately 1% of the population and leads to impairments in social interaction, communication and restricted...
We present a new method to identify anatomical subnetworks of the human connectome that are optimally predictive of targeted clinical variables, devel...
Although standard behavioral interventions for autism spectrum disorder (ASD) are effective therapies for social deficits, they face criticism for bei...
The main aim of this research work was to develop and validate a novel graphical user interface based hierarchical fuzzy autism detection tool named a...
The identification of disease-related genes and disease mechanisms is an important research goal; many studies have approached this problem by analysi...
In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the bu...
In recent decades, artificial intelligence and machine learning have played a significant role in increasing the efficiency of processes across a wide...
Autism Spectrum Disorder (ASD) is one of the fastest growing developmental disability diagnosis. General practitioners (GPs) and family physicians are...
Algorithms that learn through environmental interaction and delayed rewards, or reinforcement learning (RL), increasingly face the challenge of scalin...