Latest AI and machine learning research in adhd/add for healthcare professionals.
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the risk ADHD-associated variants and genes with significant P-values, they may neglect the combined effect of multiple variants with insignificant P-values. Here, we proposed a convolutional neural network (CNN) to classify 1033 individuals diagnosed wi...
This paper proposed an end-to-end road crack segmentation model based on attention mechanism and deep FCN with generative adversarial learning. We create a segmentation network by introducing a visual attention mechanism and residual module to a fully convolutional network(FCN) to capture richer local features and more global semantic features and get a better segment result. Besides, we use an ad...
Image-based cell phenotyping is an important and open problem in computational pathology. The two principal challenges are: 1) making the cell cluster...
Computer Assisted Diagnosis (CAD) based on brain Magnetic Resonance Imaging (MRI) is a popular research field for the computer science and medical eng...
Producing findable, accessible, interoperable and reusable (FAIR) data cannot be accomplished solely by data curators in all disciplines. In biology, ...
An increasing proportion of decisions, design choices, and predictions are being made by hybrid groups consisting of humans and artificial intelligenc...
DSOs have been at the forefront of adopting technology that demonstrates value-add to their businesses. Hence, DSOs have been quick to identify artifi...
The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated w...
Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic class...
High-content imaging and single-cell genomics are two of the most prominent high-throughput technologies for studying cellular properties and function...
A fundamental problem of supervised learning algorithms for brain imaging applications is that the number of features far exceeds the number of subjec...
This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants wer...
Rapid development in computer technology has led to sophisticated methods of analyzing large datasets with the aim of improving human decision making....
Snakes can move through almost any terrain. Similarly, snake robots hold the promise as a versatile platform to traverse complex environments such as ...
PURPOSE OF REVIEW: In recent years there has been interest in the use of machine learning in suicide research in reaction to the failure of traditiona...
Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also ad...
Can artificial intelligence (AI) develop the potential to be our partner, and will we be as sensitive to its social signals as we are to those of huma...
MOTIVATION: In evidence-based medicine, defining a clinical question in terms of the specific patient problem aids the physicians to efficiently ident...
The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. ...
Compounded medicinal products should be prepared using an appropriate quality-assurance system. Cleaning and disinfection, as part of this system, are...