Background and objective Speech disorders are a common presenting concern to paediatricians. Yet evidence to guide detection and speech sound therapy referral of cases at risk for persistent speech ...

Hundreds of genes have been linked to autism, yet the precise molecular and cellular mechanisms behind it remain largely unclear. A new study published in Nature, led by Gaia Novarino at the Institute ...

Abstract: We propose ABA-RAG, a retrieval-augmented generation (RAG) framework specifically tailored for applied behavior analysis (ABA) interventions, which integrates real-time emotional and ...

The Graduate Certificate in Applied Behavior Analysis in the Department of Early Childhood, Multilingual, and Special Education is designed to meet the needs of graduate students seeking to study ...

Most ABA practices have a website. Most have a Google Business Profile. And most are invisible to the families who need them. Local SEO for ABA practices works differently than for dentists or ...

Before students can appreciate that a heart valve is a masterpiece of engineering or notice what isn’t narrated in The Great Gatsby, they need sustained focus. Unfortunately, sustained attention is ...

Post-stroke cognitive impairment (PSCI) affects ~40% of survivors, hindering recovery. Dual-task training (combining cognitive and motor tasks) may help, but its superiority over single-task training ...

The “Year 2 Report on the Impact of AI on the Practice of Law,” is the final report from the ABA Task Force on Law and Artificial Intelligence. The report includes programs from various law schools ...

CHICAGO, Dec. 15, 2025 — The American Bar Association’s Task Force on Law and Artificial Intelligence released its final report recently. The AI Task Force “Year 2 Report on the Impact of AI on the ...

Background: Persons with chronic kidney disease (CKD) and type 2 diabetes (T2D) face high but modifiable risks of incident heart failure (HF). The HFpEF-ABA algorithm, originally developed for HFpEF ...

Abstract: Shared training approaches, such as multi-task learning (MTL) and gradient-based meta-learning, are widely used in various machine learning applications, but they often suffer from negative ...