Autism

Action Recognition of Lower Limbs Based on Surface Electromyography Weighted Feature Method.

To improve the recognition rate of lower limb actions based on surface electromyography (sEMG), an effective weighted feature method is proposed, and an improved genetic algorithm support vector machine (IGA-SVM) is designed in this paper. First, for the problem of high feature redundancy and low discrimination in the surface electromyography feature extraction process, the weighted feature method...

Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms.

OBJECTIVE: To develop and validate deep learning (DL) methods for diagnosing autism spectrum disorder (ASD) based on conventional MRI (cMRI) and apparent diffusion coefficient (ADC) images.

Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.

Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extens...

Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study.

BACKGROUND: Delays in the diagnosis of genetic syndromes are common, particularly in low and middle-income countries with limited access to genetic sc...

Identification of Autistic Risk Candidate Genes and Toxic Chemicals via Multilabel Learning.

As a group of complex neurodevelopmental disorders, autism spectrum disorder (ASD) has been reported to have a high overall prevalence, showing an unp...

English Feature Recognition Based on GA-BP Neural Network Algorithm and Data Mining.

With the development of society and the promotion of science and technology, English, as the largest universal language in the world, is used by more ...

Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.

BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a si...

Predicting phenotypes from genetic, environment, management, and historical data using CNNs.

Convolutional Neural Networks (CNNs) can perform similarly or better than standard genomic prediction methods when sufficient genetic, environmental, ...

Rosetta:MSF:NN: Boosting performance of multi-state computational protein design with a neural network.

Rational protein design aims at the targeted modification of existing proteins. To reach this goal, software suites like Rosetta propose sequences to ...

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens.

Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable...

Systematic review of Pharmacogenomics Knowledgebase evidence for pharmacogenomic links to the dopamine reward pathway for heroin dependence.

Genetics play an important role in opioid use disorder (OUD); however, few specific gene variants have been identified. Therefore, there is a need to ...

Optimization and Simulation of Manuscript Management System Based on Fuzzy Genetic Neural Network.

Manuscript management plays an important role in the whole periodical industry. Journals and magazine society receive different types of contribution ...

Identification of conserved transcriptome features between humans and Drosophila in the aging brain utilizing machine learning on combined data from the NIH Sequence Read Archive.

Aging is universal, yet characterizing the molecular changes that occur in aging which lead to an increased risk for neurological disease remains a ch...

Business English Translation Model Based on BP Neural Network Optimized by Genetic Algorithm.

In recent years, most of the communication places are using business English manual simultaneous interpretation or electronic equipment translation. I...

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is s...

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning.

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestation...

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review.

Research on affective communication for socially assistive robots has been conducted to enable physical robots to perceive, express, and respond emoti...

Decision-Making Model of Product Modeling Big Data Design Scheme Based on Neural Network Optimized by Genetic Algorithm.

At present, machine learning artificial neural network technology, as one of the core technologies of enterprises, has received unprecedented attentio...

Improving Measures of Chemical Structural Similarity Using Machine Learning on Chemical-Genetic Interactions.

A common strategy for identifying molecules likely to possess a desired biological activity is to search large databases of compounds for high structu...

Gene Mutation Classification through Text Evidence Facilitating Cancer Tumour Detection.

A cancer tumour consists of thousands of genetic mutations. Even after advancement in technology, the task of distinguishing genetic mutations, which ...