Autism

A graph neural network-based model with out-of-distribution robustness for enhancing antiretroviral therapy outcome prediction for HIV-1.

Predicting the outcome of antiretroviral therapies (ART) for HIV-1 is a pressing clinical challenge, especially when the ART includes drugs with limited effectiveness data. This scarcity of data can arise either due to the introduction of a new drug to the market or due to limited use in clinical settings, resulting in clinical dataset with highly unbalanced therapy representation. To tackle this ...

Applying artificial intelligence to uncover the genetic landscape of coagulation factors.

Artificial intelligence (AI) is rapidly advancing our ability to identify and interpret genetic variants associated with coagulation factor deficiencies. This review introduces AI, with a specific focus on machine learning (ML) methods, and examines its applications in the field of coagulation genetics over the past decade. We observed a significant increase in AI-related publications, with a focu...

A machine learning approach for estimating Eastern Asian origins from massive screening of Y chromosomal short tandem repeats polymorphisms.

Inferring the ancestral origin of DNA evidence recovered from crime scenes is crucial in forensic investigations, especially in the absence of a direc...

Boosting skin cancer diagnosis accuracy with ensemble approach.

Skin cancer is common and deadly, hence a correct diagnosis at an early age is essential. Effective therapy depends on precise classification of the s...

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) affect 4.7% of the global population and are associated with delays in brain development and a spectrum of impairm...

Understanding the impacts of drought on peanuts L.): exploring physio-genetic mechanisms to develop drought-resilient peanut cultivars.

Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production oc...

Diagnostic and prognostic perspectives of Fabry disease via fiber evanescent wave spectroscopy advanced by machine learning.

Fabry disease (FD) is a rare disorder resulting from a genetic mutation characterized by the accumulation of sphingolipids in various cells throughout...

A Trustworthy Curriculum Learning Guided Multi-Target Domain Adaptation Network for Autism Spectrum Disorder Classification.

Domain adaptation has demonstrated success in classification of multi-center autism spectrum disorder (ASD). However, current domain adaptation method...

Early detection of autism spectrum disorder: gait deviations and machine learning.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder diagnosed by clinicians and experts through questionnaires, observations, and intervie...

Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning.

Model optimization is a problem of great concern and challenge for developing an image classification model. In image classification, selecting the ap...

Neural correlates of facial recognition deficits in autism spectrum disorder: a comprehensive review.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by significant impairments in social interaction, often manifested in f...

Developing a simplified measure to predict the risk of autism spectrum disorders: Abbreviating the M-CHAT-R using a machine learning approach in China.

BACKGROUND: Early screening for autism spectrum disorder (ASD) is crucial, yet current assessment tools in Chinese primary child care are limited in e...

Differential gray matter correlates and machine learning prediction of abuse and internalizing psychopathology in adolescent females.

Childhood abuse represents one of the most potent risk factors for the development of psychopathology during childhood, accounting for 30-60% of the r...

PFSH-Net: Parallel frequency-spatial hybrid network for segmentation of kidney stones in pre-contrast computed tomography images of dogs.

Kidney stone is a common urological disease in dogs and can lead to serious complications such as pyelonephritis and kidney failure. However, manual d...

Why robot embodiment matters: questions of disability, race and intersectionality in the design of social robots.

A growing minority of those with disabilities are people of color (POC), with, for example, autism diagnosis rates now higher for children of color th...

Development of an individualized dementia risk prediction model using deep learning survival analysis incorporating genetic and environmental factors.

BACKGROUND: Dementia is a major public health challenge in modern society. Early detection of high-risk dementia patients and timely intervention or t...

Diagnosis of Autism Spectrum Disorder (ASD) by Dynamic Functional Connectivity Using GNN-LSTM.

Early detection of autism spectrum disorder (ASD) is particularly important given its insidious qualities and the high cost of the diagnostic process....

Objective approach to diagnosing attention deficit hyperactivity disorder by using pixel subtraction and machine learning classification of outpatient consultation videos.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common childhood neurodevelopmental disorder, affecting between 5% and 7% of school-a...

Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.

A complex interplay of genetic and environmental factors influences bacterial growth. Understanding these interactions is crucial for insights into co...

ShinyGS-a graphical toolkit with a serial of genetic and machine learning models for genomic selection: application, benchmarking, and recommendations.

Genomic prediction is a powerful approach for improving genetic gain and shortening the breeding cycles in animal and crop breeding programs. A series...