Latest AI and machine learning research in autism for healthcare professionals.
Timely identification of COVID-19 outpatients who are at risk of hospitalization is critical for preventing clinical deterioration and optimizing healthcare resources. Although machine-learning models have demonstrated high predictive accuracy, their limited interpretability often hinders clinical adoption. This study aims to develop a hybrid explainable framework that combines the predictive stre...
The ability to predict individual genetic susceptibility to a complex trait disease is a major challenge in modern medicine. One approach to addressing this challenge utilizes an additive combination of contributions from a large number of single nucleotide polymorphisms (SNPs), with weights derived from Genome Wide Association Studies (GWAS). While this approach is somewhat successful in predicti...
BACKGROUND: Internalizing disorders are among the most common psychiatric conditions in adolescence, often associated with long-term adverse outcomes....
BACKGROUND: Tumor evolution is a spatiotemporal dynamic process orchestrated by the interplay of genetic mutations, epigenetic reprogramming, and bidi...
Differentiating between bipolar disorder (BD) and schizophrenia (SZ) is challenging due to overlapping clinical symptoms and shared genetic risks, res...
Over recent years, several deep learning (DL) models have been presented to predict colorectal cancer (CRC) patient survival directly from haematoxyli...
Inferring the genetic structure at the subpopulation level is crucial for understanding the demographic histories that shape genetic diversity. Among ...
OBJECTIVE: Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention...
Endometriosis (EMs) is a common chronic inflammatory gynecological disorder. But the exact pathogenetic mechanism of the disease is not clear, with so...
Bone metastasis affects approximately 40% of patients with non-small cell lung cancer (NSCLC), significantly impacting patient survival and prognosis....
Federated learning (FL) enables collaborative medical image analysis across decentralized institutions while preserving data privacy. However, real-wo...
INTRODUCTION: Steroid-resistant nephrotic syndrome (SRNS) is the leading cause of chronic glomerular disease in individuals under 25 years of age. Bia...
BACKGROUND: CRISPR-based genetic screening has become a central methodology in functional genomics, enabling systematic interrogation of gene function...
Traditional subjective measures are limited in the insight they provide into underlying behavioral differences associated with autism and, accordingly...
Neurofeedback therapy (NFT) has emerged as a promising noninvasive intervention for autism spectrum disorder (ASD), targeting core symptoms such as so...
Introduction. Misinformation is a barrier to immunization. The objective was to describe and categorize vaccine-related myths reported by healthcare p...
BACKGROUND: C-X-C motif chemokine receptor 4 (CXCR4)-directed radiopharmaceutical therapy (RPT) represents a promising option for hematologic malignan...
PURPOSE OF REVIEW: Emerging biobank resources allow large-scale integration of eye-specific phenotypes with clinical, genomic, and multiomic data. Thi...
Many non-model rodent species are inaccessible to genetic engineering due to our limited understanding of their reproductive biology. Here, we present...
Parkinson's disease (PD) risk and progression are influenced by a complex interplay of genetic, environmental, and internal factors. Environmental exp...