Latest AI and machine learning research in practice management for healthcare professionals.
Circular RNAs (circRNAs) are important components of the non-coding RNA regulatory network. Previous circRNA identification primarily relies on high-throughput RNA sequencing (RNA-seq) data combined with alignment-based algorithms that detect back-splicing signals. However, these methods face several limitations: they can't predict circRNAs directly from genomic DNA sequences and relies heavily ...
Recent advances in video generation techniques have given rise to an emerging paradigm of generative video coding, aiming to achieve semantically accurate reconstructions in Ultra-Low Bitrate (ULB) scenarios by leveraging strong generative priors. However, most existing methods are limited by domain specificity (e.g., facial or human videos) or an excessive dependence on high-level text guidance...
Recent advances in video generation techniques have given rise to an emerging paradigm of generative video coding, aiming to achieve semantically ac...
With the emergence of 6G networks and proliferation of visual applications, efficient image transmission under adverse channel conditions is critica...
Cost models in healthcare research must balance interpretability, accuracy, and parameter consistency. However, interpretable models often struggle ...
This study investigates the feasibility and performance of federated learning (FL) for multi-label ICD code classification using clinical notes from...
This study evaluates how well large language models (LLMs) can classify ICD-10 codes from hospital discharge summaries, a critical but error-prone t...
The complexity of mental healthcare billing enables anomalies, including fraud. While machine learning methods have been applied to anomaly detectio...
Automatic medical coding has the potential to ease documentation and billing processes. For this task, transparency plays an important role for medi...
In recent years, compressed domain semantic inference has primarily relied on learned image coding models optimized for mean squared error (MSE). Ho...
Data distribution across different facilities offers benefits such as enhanced resource utilization, increased resilience through replication, and i...
Utilizing thermal infrared facial imaging for fever screening in public spaces has become a common strategy to curb the spread of influenza viruses. H...
Anxiety disorders are the most prevalent type of mental health disorders and are characterised by excessive fear and worry. Despite affecting one in f...
Predictive coding networks trained with equilibrium propagation are neural models that perform inference through an iterative energy minimization pr...
Family caregivers of individuals with Alzheimer's Disease and Related Dementia (AD/ADRD) face significant emotional and logistical challenges that p...
The rise of generative AI agents has reshaped human-computer interaction and computer-supported cooperative work by shifting users' roles from direc...
The Medical Information Mart for Intensive Care (MIMIC) datasets have become the Kernel of Digital Health Research by providing freely accessible, d...
Feature coding has become increasingly important in scenarios where semantic representations rather than raw pixels are transmitted and stored. Howe...
Coding remains one of the most fundamental modes of interaction between humans and machines. With the rapid advancement of Large Language Models (LL...
Gaussian and Laplacian entropy models are proved effective in learned point cloud attribute compression, as they assist in arithmetic coding of late...