Latest AI and machine learning research in adhd/add for healthcare professionals.
The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication, we describe ongoing changes to our production pipeline to limit the sequences available in UniProtKB to high-quality, non-redundant reference proteomes. We continu...
Reducing computational costs is an important issue for development of embedded systems. Binary-weight Neural Networks (BNNs), in which weights are binarized and activations are quantized, are employed to reduce computational costs of various kinds of applications. In this paper, a design methodology of hardware architecture for inference engines is proposed to handle modern BNNs with two operati...
The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these d...
From rodents to humans, animals constantly face a central question: is the reward worth the effort? Effort and reward sensitivity in such situations v...
Although developmental language delays affect approximately 10% of children in the general population, the neurodevelopmental mechanisms that support ...
Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CU...
Cancer arises from oncogenic clones, yet the dynamic mechanisms governing their stepwise evolution toward malignancy remain incompletely understood. H...
Attention-deficit/hyperactivity disorder and anxiety disorders are highly prevalent in youth and are characterized by substantial heterogeneity and fr...
Decisions are typically viewed as arising from a sequential process: perception, decision, and then action. However, an alternative perspective, drawi...
Artificial intelligence plays an ever-greater role in preclinical drug development, ranging from target identification and molecule design to ADME-Tox...
Populations of neurons in motor cortex signal voluntary movement. Most classic neural encoding models and current brain-computer interface decoders as...
Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in the U.S., and the stimulant and nonstimulant medicat...
Genomic sequence-to-function models have emerged as powerful tools for deciphering cis-regulatory grammar to advance our understanding of disease biol...
Recent studies have demonstrated strong associations between the changes in dynamic functional connectivity (FC) and both behavioral and cognitive fun...
Multimodal neural networks integrating protein language models (PLMs) with structure-derived features are increasingly common for predicting mutation ...
Assessing the degree and characteristics of consciousness is central to caring for patients with Disorders of Consciousness (DoC), yet current standar...
Microbiome beta diversity analysis relies on distance-based methods including PERMANOVA combined with fixed ecological distance metrics (Bray-Curtis, ...
Alzheimer’s disease (AD) is characterized by progressive cognitive decline and increased seizure susceptibility; yet both the mechanistic and temporal...
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in ...
The prognostic significance of tumor-infiltrating lymphocytes (TILs) in breast cancer has been recognized for over a decade. Although histology-based ...