Preserving privacy in large language models: A survey on current threats and solutions
Large Language Models (LLMs) represent a significant advancement in artificial
intelligence, finding applications across various domains. However, their reliance on …
intelligence, finding applications across various domains. However, their reliance on …
Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges
This paper presents a comprehensive systematic review of generative models (GANs, VAEs,
DMs, and LLMs) used to synthesize various medical data types, including imaging …
DMs, and LLMs) used to synthesize various medical data types, including imaging …
Synthetic Health Data: Real Ethical Promise and Peril
Researchers and practitioners are increasingly using machine‐generated synthetic data as
a tool for advancing health science and practice, by expanding access to health data while …
a tool for advancing health science and practice, by expanding access to health data while …
Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes
The development of large language models tailored for handling patients' clinical notes is
often hindered by the limited accessibility and usability of these notes due to strict privacy …
often hindered by the limited accessibility and usability of these notes due to strict privacy …
[HTML][HTML] The impact of collaborative documentation on person-centered care: Textual analysis of clinical notes
Background Collaborative documentation (CD) is a behavioral health practice involving
shared writing of clinic visit notes by providers and consumers. Despite widespread …
shared writing of clinic visit notes by providers and consumers. Despite widespread …
A Review on Generative AI Models for Synthetic Medical Text, Time Series, and Longitudinal Data
This paper presents the results of a novel scoping review on the practical models for
generating three different types of synthetic health records (SHRs): medical text, time series …
generating three different types of synthetic health records (SHRs): medical text, time series …
Preserving Privacy During Reinforcement Learning With AI Feedback
Leveraging the scalable efficacy of reinforcement learning from AI feedback (RLAIF), large
language models (LLMs) can be refined toward human intent alignment. While current …
language models (LLMs) can be refined toward human intent alignment. While current …
Enhancing Skin Cancer Detection with Multimodal Data Integration: A Combined Approach Using Images and Clinical Notes
V Chakkarapani, S Poornapushpakala, S Suresh - SN Computer Science, 2025 - Springer
Skin cancer is one of the most common cancers worldwide where early detection is crucial
for effectively diagnosing and treatment. Traditional diagnostic methods largely depend on …
for effectively diagnosing and treatment. Traditional diagnostic methods largely depend on …
A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications
Data-driven technologies have improved the efficiency, reliability and effectiveness of
healthcare services, but come with an increasing demand for data, which is challenging due …
healthcare services, but come with an increasing demand for data, which is challenging due …
[PDF][PDF] Generating English Synthetic Documents with Clinical Keywords: A Privacy-Sensitive Methodology
Abstract Electronic Health Records (EHR) store valuable patient-staff interaction data. These
notes, often unstructured to save healthcare personnel time, can be challenging to analyze …
notes, often unstructured to save healthcare personnel time, can be challenging to analyze …