HIV/AIDS

LLM-Assisted Taxonomy and Temporal Analysis of Provider Questions About HIV in provider-to-provider telehealth

Ongoing education in HIV care is limited for many healthcare providers working in rural and non-academic settings, which can reduce patients’ access to high-quality care. To guide targeted tele-mentoring and continuing education, we analyzed questions submitted by clinicians during Extension for Community Healthcare Outcomes (ECHO) sessions to characterize learning needs and thematic trends. We re...

TabGraphSyn: Graph-Guided Latent Diffusion for High-Fidelity and Privacy-Conscious Clinical Data Generation

The critical need for accessible patient data in clinical research is often hindered by privacy regulations and data scarcity. While synthetic data generation offers a promising solution, existing generative models face key limitations. GANs can suffer from training instability, while diffusion models typically process records independently and often neglect the local neighborhood structure of the...

DMSA: A Decentralized Microservice Architecture for Edge Networks

The dispersed node locations and complex topologies of edge networks, combined with intricate dynamic microservice dependencies, render traditional ...

HIV multidrug class resistance prediction with a time sliding anchor approach.

MOTIVATION: The emergence of multidrug class resistance (MDR) in Human Immunodeficiency Virus (HIV) is a rare but significant challenge in antiretrovi...

Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis.

INTRODUCTION: Tuberculous meningitis (TBM) leads to high mortality, especially amongst individuals with HIV. Predicting the incidence of disease-relat...

Artificial intelligence and assisted reproductive technology: A comprehensive systematic review.

The objective of this review is to evaluate the contributions of Artificial Intelligence (AI) to Assisted Reproductive Technologies (ART), focusing on...

Establishment and Validation of a Machine-Learning Prediction Nomogram Based on Lymphocyte Subtyping for Intra-Abdominal Candidiasis in Septic Patients.

This study aimed to develop and validate a nomogram based on lymphocyte subtyping and clinical factors for the early and rapid prediction of Intra-abd...

Neural-WDRC: A Deep Learning Wide Dynamic Range Compression Method Combined With Controllable Noise Reduction for Hearing Aids.

Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so th...

Pan-infection Foundation Framework Enables Multiple Pathogen Prediction

Host-response-based diagnostics can improve the accuracy of diagnosing bacterial and viral infections, thereby reducing inappropriate antibiotic pre...

Human-Centered Design for AI-based Automatically Generated Assessment Reports: A Systematic Review

This paper provides a comprehensive review of the design and implementation of automatically generated assessment reports (AutoRs) for formative use...

Predicting Long Term Sequential Policy Value Using Softer Surrogates

Off-policy policy evaluation (OPE) estimates the outcome of a new policy using historical data collected from a different policy. However, existing ...

Generating Completions for Fragmented Broca's Aphasic Sentences Using Large Language Models

Broca's aphasia is a type of aphasia characterized by non-fluent, effortful and fragmented speech production with relatively good comprehension. Sin...

RCLMuFN: Relational Context Learning and Multiplex Fusion Network for Multimodal Sarcasm Detection

Sarcasm typically conveys emotions of contempt or criticism by expressing a meaning that is contrary to the speaker's true intent. Accurate detectio...

Distillation of Diffusion Features for Semantic Correspondence

Semantic correspondence, the task of determining relationships between different parts of images, underpins various applications including 3D recons...

AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Large language models (LLMs) have enabled the creation of multi-modal LLMs that exhibit strong comprehension of visual data such as images and video...

Stain-aware Domain Alignment for Imbalance Blood Cell Classification

Blood cell identification is critical for hematological analysis as it aids physicians in diagnosing various blood-related diseases. In real-world s...

Explaining the Unexplained: Revealing Hidden Correlations for Better Interpretability

Deep learning has achieved remarkable success in processing and managing unstructured data. However, its "black box" nature imposes significant limi...

Survival causal rule ensemble method considering the main effect for estimating heterogeneous treatment effects.

With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship b...

[Investigation of the impact of the deep learning based CT fractional flow reserve on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease].

To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patie...

[Study on predicting new onset heart failure events in patients with hypertrophic cardiomyopathy using machine learning algorithms based on clinical and magnetic resonance features].

To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magne...