Neurology

Autism

Latest AI and machine learning research in autism for healthcare professionals.

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Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity.

Machine learning methods, such as deep learning, show promising results in the medical domain. Howev...

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance...

[Therapeutic use of robotics in children with Autism Spectrum Disorder].

INTRODUCTION: Robot-assisted Therapy (RAT) can improve the behavior of children with Autism Spectrum...

Identification of haploinsufficient genes from epigenomic data using deep forest.

Haploinsufficiency, wherein a single allele is not enough to maintain normal functions, can lead to ...

Bioinformatics and machine learning methodologies to identify the effects of central nervous system disorders on glioblastoma progression.

Glioblastoma (GBM) is a common malignant brain tumor which often presents as a comorbidity with cent...

Automatically Evolving Texture Image Descriptors Using the Multitree Representation in Genetic Programming Using Few Instances.

The performance of image classification is highly dependent on the quality of the extracted features...

PharmGKB, an Integrated Resource of Pharmacogenomic Knowledge.

The Pharmacogenomics Knowledgebase (PharmGKB) is an integrated online knowledge resource for the und...

Predictive Models of Genetic Redundancy in Arabidopsis thaliana.

Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one...

Towards realizing the vision of precision medicine: AI based prediction of clinical drug response.

Accurate and individualized prediction of response to therapies is central to precision medicine. Ho...

Brief Report: Neuroimaging Endophenotypes of Social Robotic Applications in Autism Spectrum Disorder.

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes us...

Probabilistic Contextual and Structural Dependencies Learning in Grammar-Based Genetic Programming.

Genetic Programming is a method to automatically create computer programs based on the principles of...

Prediction of fetal weight based on back propagation neural network optimized by genetic algorithm.

Fetal weight is an important index to judge fetal development and ensure the safety of pregnant wome...

[Application of the artificial intelligence-rapid whole-genome sequencing diagnostic system in the neonatal/pediatric intensive care unit].

Pediatric patients in the neonatal intensive care unit (NICU) and the pediatric intensive care unit ...

Future perspectives of robot psychiatry: can communication robots assist psychiatric evaluation in the COVID-19 pandemic era?

PURPOSE OF REVIEW: Direct face-to-face interview between a psychiatrist and a patient is crucial in ...

Opportunities and challenges for the computational interpretation of rare variation in clinically important genes.

Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of ...

A machine-learning approach to map landscape connectivity in with genetic and environmental data.

Mapping landscape connectivity is important for controlling invasive species and disease vectors. Cu...

Categorization of birth weight phenotypes for inclusion in genetic evaluations using a deep neural network.

Birth weight (BW) serves as a valuable indicator of the economically relevant trait of calving ease ...

An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis.

OBJECTIVE: Tuberculosis is the leading cause of death from a single infectious agent. The emergence ...

CRISPRidentify: identification of CRISPR arrays using machine learning approach.

CRISPR-Cas are adaptive immune systems that degrade foreign genetic elements in archaea and bacteria...

Predicting regulatory variants using a dense epigenomic mapped CNN model elucidated the molecular basis of trait-tissue associations.

Assessing the causal tissues of human complex diseases is important for the prioritization of trait-...

m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.

N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pi...

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