Practice Management

Latest AI and machine learning research in practice management for healthcare professionals.

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Baichuan-M1: Pushing the Medical Capability of Large Language Models

The current generation of large language models (LLMs) is typically designed for broad, general-pu...

Simplifying DINO via Coding Rate Regularization

DINO and DINOv2 are two model families being widely used to learn representations from unlabeled i...

Conditional Latent Coding with Learnable Synthesized Reference for Deep Image Compression

In this paper, we study how to synthesize a dynamic reference from an external dictionary to perfo...

Life-Code: Central Dogma Modeling with Multi-Omics Sequence Unification

The interactions between DNA, RNA, and proteins are fundamental to biological processes, as illust...

Rateless Joint Source-Channel Coding, and a Blueprint for 6G Semantic Communications System Design

This paper introduces rateless joint source-channel coding (rateless JSCC). The code is rateless i...

Explainable and externally validated machine learning for neuropsychiatric diagnosis via electrocardiograms

Electrocardiogram (ECG) analysis has emerged as a promising tool for identifying physiological cha...

Deep Learning-based Event Data Coding: A Joint Spatiotemporal and Polarity Solution

Neuromorphic vision sensors, commonly referred to as event cameras, have recently gained relevance...

The Impact of AI-driven Remote Patient Monitoring on Cancer Care: A Systematic Review.

The coronavirus disease 2019 (COVID-19) pandemic necessitated a shift in healthcare delivery, emphas...

Feb 2025 39890180
A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes.

BACKGROUND: International Classification of Diseases (ICD) codes utilized for congenital heart defec...

Feb 2025 39890469
The Gap Between Principle and Practice of Lossy Image Coding

Lossy image coding is the art of computing that is principally bounded by the image's rate-distort...

Towards Loss-Resilient Image Coding for Unstable Satellite Networks

Geostationary Earth Orbit (GEO) satellite communication demonstrates significant advantages in eme...

RWZC: A Model-Driven Approach for Learning-based Robust Wyner-Ziv Coding

In this paper, a novel learning-based Wyner-Ziv coding framework is considered under a distributed...

Joint Transmission and Deblurring: A Semantic Communication Approach Using Events

Deep learning-based joint source-channel coding (JSCC) is emerging as a promising technology for e...

A Brain Age Residual Biomarker (BARB): Leveraging MRI-Based Models to Detect Latent Health Conditions in U.S. Veterans

Age prediction using brain imaging, such as MRIs, has achieved promising results, with several stu...

Unified Coding for Both Human Perception and Generalized Machine Analytics with CLIP Supervision

The image compression model has long struggled with adaptability and generalization, as the decode...

SNR-EQ-JSCC: Joint Source-Channel Coding with SNR-Based Embedding and Query

Coping with the impact of dynamic channels is a critical issue in joint source-channel coding (JSC...

SCSC: A Novel Standards-Compatible Semantic Communication Framework for Image Transmission

Joint source-channel coding (JSCC) is a promising paradigm for next-generation communication syste...

Compressed Domain Prior-Guided Video Super-Resolution for Cloud Gaming Content

Cloud gaming is an advanced form of Internet service that necessitates local terminals to decode w...

Biological profits of irrational computations in the orbitofrontal cortex

Making good decisions is essential for survival and success, yet humans and animals often exhibit pe...

Recon8D: A metabolic regulome network from oct-omics and machine learning

To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic v...

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