There is an ongoing debate whether a differentiation of autistic subtypes, especially between Asperger Syndrome (AS) and high-functioning-autism (HFA) is possible and if so, whether it is a categorical or dimensional one. The aim of this study was to examine the possible clustering of responses in different symptom domains without making any assumption concerning diagnostic appreciation. About 140 children and adolescents, incorporating 52 with a diagnosis of AS, 44 with HFA, 8 with atypical autism and 36 with other diagnoses, were examined. Our study does not support the thesis that autistic disorders are discrete phenotypes. On the contrary, it provides evidence that e.g. AS and autism are not qualitatively distinct disorders, but rather different quantitative manifestations of the same disorder.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s10803-010-0939-5 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An EEG-based framework for automated discrimination of conversion to Alzheimer's disease in patients with amnestic mild cognitive impairment: an 18-month longitudinal study.
Front Aging Neurosci
January 2025
Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Background: As a clinical precursor to Alzheimer's disease (AD), amnestic mild cognitive impairment (aMCI) bears a considerably heightened risk of transitioning to AD compared to cognitively normal elders. Early prediction of whether aMCI will progress to AD is of paramount importance, as it can provide pivotal guidance for subsequent clinical interventions in an early and effective manner.
Methods: A total of 107 aMCI cases were enrolled and their electroencephalogram (EEG) data were collected at the time of the initial diagnosis.
The application of machine learning approaches to classify and predict fertility rate in Ethiopia.
Sci Rep
January 2025
Department of Clinical Pharmacy, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Integrating machine learning (ML) models into healthcare systems is a rapidly evolving field with the potential to revolutionize care delivery. This study aimed to classify fertility rates and identify significant predictors using ML models among reproductive women in Ethiopia. This study utilized eight ML models in 5864 reproductive-age women using Ethiopian Demographic Health Survey (EDHS), 2019 data.
View Article and Find Full Text PDFA multi-modal dental dataset for semi-supervised deep learning image segmentation.
Sci Data
January 2025
School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China.
In response to the increasing prevalence of dental diseases, dental health, a vital aspect of human well-being, warrants greater attention. Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing and treating dental conditions. Additionally, deep learning for tooth segmentation can focus on relevant treatment information and localize lesions.
View Article and Find Full Text PDFMyocardial synchronized exercise and prognosis in patients with heart failure with preserved ejection fraction assessed by two-dimensional ultrasound speckle tracking stratified strain imaging.
Medicine (Baltimore)
January 2025
Department of Ultrasound, JinHua Municipal Central Hospital, Jinhua, Zhejiang, China.
To evaluate myocardial synchronized exercise and clinical prognosis in patients with heart failure preserved ejection fraction (HFpEF), we utilized two-dimensional speckle tracking (2D-STI) stratified strain imaging. We retrospectively summarized 146 patients diagnosed with HFpEF in our hospital from January 2022 to January 2023. 2D-STI combined with stratified strain imaging was used to measure the overall left ventricular global longitudinal strain (LVGLS), the sub-endocardium, mid-myocardium, sub-epicardium LS of the left ventricle, as well as the basal, intermediate, and apical LS, the peak strain dispersion (PSD) and the transmural pressure difference, the postsystolic shortening (PSS), and early systolic lengthening.
View Article and Find Full Text PDFSensing array based on imidazole-regulated Cu@MOFs nanozymes with enhanced laccase-like activity for the discrimination of phenolic pollutants.
Anal Chim Acta
February 2025
School of the Environment and Safety Engineering, School of the Emergency Management, Jiangsu University, Zhenjiang, 212013, China; Center for Medical Laboratory Science, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533000, China; Key Laboratory of Clinical Molecular Diagnosis and Research for High Incidence Diseases in Western Guangxi, Guangxi, 533000, China. Electronic address:
Background: Phenolic pollutants with high toxicity and low biodegradability can disrupt environmental balance and severely affect human health, whereas existing methods are difficult to implement the rapid and high-throughput detection of multiple phenolic pollutants.
Results: Herein, we developed a four-dimensional colorimetric sensor array based on imidazole-modulated Cu@MOFs for distinguishing and determining phenolic pollutants. Wherein, four Cu@MOFs (ATP@Cu, ADP@Cu, AMP@Cu, and GMP@Cu) nanozyme with laccase-like activity were firstly prepared, and a novel strategy of imidazole-containing molecules-regulated was proposed to improve the laccase-like activity of Cu@MOFs nanozymes.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!