ADHD/ADD

HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks

Identifying unusual brain activity is a crucial task in neuroscience research, as it aids in the early detection of brain disorders. It is common to represent brain networks as graphs, and researchers have developed various graph-based machine learning methods for analyzing them. However, the majority of existing graph learning tools for the brain face a combination of the following three key li...

KIPPS: Knowledge infusion in Privacy Preserving Synthetic Data Generation

The integration of privacy measures, including differential privacy techniques, ensures a provable privacy guarantee for the synthetic data. However, challenges arise for Generative Deep Learning models when tasked with generating realistic data, especially in critical domains such as Cybersecurity and Healthcare. Generative Models optimized for continuous data struggle to model discrete and non...

Active Learning to Guide Labeling Efforts for Question Difficulty Estimation

In recent years, there has been a surge in research on Question Difficulty Estimation (QDE) using natural language processing techniques. Transforme...

Biomedical knowledge graph-optimized prompt generation for large language models.

MOTIVATION: Large language models (LLMs) are being adopted at an unprecedented rate, yet still face challenges in knowledge-intensive domains such as ...

Floating-Point Multiply-Add with Approximate Normalization for Low-Cost Matrix Engines

The widespread adoption of machine learning algorithms necessitates hardware acceleration to ensure efficient performance. This acceleration relies ...

Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis

Deep neural networks have demonstrated remarkable effectiveness across a wide range of tasks such as semantic segmentation. Nevertheless, these netw...

AltCanvas: A Tile-Based Image Editor with Generative AI for Blind or Visually Impaired People

People with visual impairments often struggle to create content that relies heavily on visual elements, particularly when conveying spatial and stru...

Are gene-by-environment interactions leveraged in multi-modality neural networks for breast cancer prediction?

Polygenic risk scores (PRSs) can significantly enhance breast cancer risk prediction when combined with clinical risk factor data. While many studie...

Enhancing context models for point cloud geometry compression with context feature residuals and multi-loss

In point cloud geometry compression, context models usually use the one-hot encoding of node occupancy as the label, and the cross-entropy between t...

PICO-RAM: A PVT-Insensitive Analog Compute-In-Memory SRAM Macro with In-Situ Multi-Bit Charge Computing and 6T Thin-Cell-Compatible Layout

Analog compute-in-memory (CIM) in static random-access memory (SRAM) is promising for accelerating deep learning inference by circumventing the memo...

SwiftDiffusion: Efficient Diffusion Model Serving with Add-on Modules

Text-to-image (T2I) generation using diffusion models has become a blockbuster service in today's AI cloud. A production T2I service typically invol...

Deep Generative Replay-based Class-incremental Continual Learning in sEMG-based Pattern Recognition.

Developments in neural networks and sensing technologies have increased focus on modules for surface electromyogram (sEMG)-based pattern recognition. ...

Complexity Analysis based on Parietal Fuzzy Entropy to Facilitate ADHD Diagnosis in Young Children.

Attention deficit hyperactivity disorder (ADHD) is the most common condition affecting the development of neurons in children. Therefore, early and ac...

Neurodevelopmental disorders modeling using isogeometric analysis, dynamic domain expansion and local refinement

Neurodevelopmental disorders (NDDs) have arisen as one of the most prevailing chronic diseases within the US. Often associated with severe adverse i...

QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead

Serving LLMs requires substantial memory due to the storage requirements of Key-Value (KV) embeddings in the KV cache, which grows with sequence len...

PuFace: Defending against Facial Cloaking Attacks for Facial Recognition Models

The recently proposed facial cloaking attacks add invisible perturbation (cloaks) to facial images to protect users from being recognized by unautho...

Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review.

Machine learning (ML)-based risk prediction models hold the potential to support the health-care setting in several ways; however, use of such models ...

Classification of DNA Sequence Based on a Non-gradient Algorithm: Pseudoinverse Learners.

This chapter proposes a prototype-based classification approach for analyzing DNA barcodes that uses a spectral representation of DNA sequences and a ...

[A study of the clinical curative effect of nucleos(t)ide analogues treated to pegylated interferon-α add-on therapy in patients with chronic hepatitis B].

To investigate the hepatitis B surface antigen (HBsAg) clearance condition and its predictive factors after treatment with nucleos(t)ide analogues to...

Add-on treatment with Cerebrolysin improves clinical symptoms in patients with ALS: results from a prospective, single-center, placebo-controlled, randomized, double-blind, phase II study.

Amyotrophic lateral sclerosis (ALS) is a devastating and progressive neurodegenerative disease with limited treatment options available. Cerebrolysin ...