Cover Image

A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Kai, Mao, Rui, Lin, Qika, Ruan, Yucheng, Lan, Xiang, Feng, Mengling, Cambria, Erik
Format:	Preprint
Published:	2023
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution
by: Ruan, Yucheng, et al.
Published: (2024)

A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models
by: Lin, Qika, et al.
Published: (2025)

Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction
by: Ruan, Yucheng, et al.
Published: (2026)

A Systematic Analysis of Biases in Large Language Models
by: Zhang, Xulang, et al.
Published: (2025)

Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey
by: Lin, Qika, et al.
Published: (2024)

Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
by: Xu, Fangzhi, et al.
Published: (2023)

Exploring Cognitive and Aesthetic Causality for Multimodal Aspect-Based Sentiment Analysis
by: Xiao, Luwei, et al.
Published: (2025)

P-Transformer: A Prompt-based Multimodal Transformer Architecture For Medical Tabular Data
by: Ruan, Yucheng, et al.
Published: (2023)

Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models
by: Lin, Qika, et al.
Published: (2025)

Towards Unified Neurosymbolic Reasoning on Knowledge Graphs
by: Lin, Qika, et al.
Published: (2025)

Prediction of mortality and resource utilization in critical care: a deep learning approach using multimodal electronic health records with natural language processing techniques
by: Ruan, Yucheng, et al.
Published: (2025)

Logical Reasoning over Natural Language as Knowledge Representation: A Survey
by: Yang, Zonglin, et al.
Published: (2023)

EsurvFusion: An evidential multimodal survival fusion model based on Gaussian random fuzzy numbers
by: Huang, Ling, et al.
Published: (2024)

LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence
by: Liu, Wenjin, et al.
Published: (2025)

XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models
by: Cambria, Erik, et al.
Published: (2024)

GPTEval: A Survey on Assessments of ChatGPT and GPT-4
by: Mao, Rui, et al.
Published: (2023)

Enhancing Language Models for Robust Greenwashing Detection
by: Braun, Neil Heinrich, et al.
Published: (2026)

Deriving Strategic Market Insights with Large Language Models: A Benchmark for Forward Counterfactual Generation
by: Ong, Keane, et al.
Published: (2025)

Towards Faithful Natural Language Explanations: A Study Using Activation Patching in Large Language Models
by: Yeo, Wei Jie, et al.
Published: (2024)

DivScore: Zero-Shot Detection of LLM-Generated Text in Specialized Domains
by: Chen, Zhihui, et al.
Published: (2025)

MARS: Multi-Agent Adaptive Reasoning with Socratic Guidance for Automated Prompt Optimization
by: Zhang, Jian, et al.
Published: (2025)

ClimaEmpact: Domain-Aligned Small Language Models and Datasets for Extreme Weather Analytics
by: Varshney, Deeksha, et al.
Published: (2025)

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint
by: Du, Yanrui, et al.
Published: (2025)

From Latent Signals to Reflection Behavior: Tracing Meta-Cognitive Activation Trajectory in R1-Style LLMs
by: Du, Yanrui, et al.
Published: (2026)

Large Language Models for Few-Shot Named Entity Recognition
by: Zhao, Yufei, et al.
Published: (2018)

GEM: Empowering MLLM for Grounded ECG Understanding with Time Series and Images
by: Lan, Xiang, et al.
Published: (2025)

Self-training Large Language Models through Knowledge Detection
by: Yeo, Wei Jie, et al.
Published: (2024)

How Interpretable are Reasoning Explanations from Prompting Large Language Models?
by: Yeo, Wei Jie, et al.
Published: (2024)

Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI
by: Perera, Dilruk, et al.
Published: (2025)

Harnessing Large Language Models for Scientific Novelty Detection
by: Liu, Yan, et al.
Published: (2025)

Affective Flow Language Model for Emotional Support Conversation
by: Zou, Chenghui, et al.
Published: (2026)

An Open Source Data Contamination Report for Large Language Models
by: Li, Yucheng, et al.
Published: (2023)

Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization
by: Ong, Keane, et al.
Published: (2025)

Large Language Models for Automated Open-domain Scientific Hypotheses Discovery
by: Yang, Zonglin, et al.
Published: (2023)

Explainable Natural Language Processing for Corporate Sustainability Analysis
by: Ong, Keane, et al.
Published: (2024)

Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation
by: Nadeem, Mohammad, et al.
Published: (2024)

S3-CoT: Self-Sampled Succinct Reasoning Enables Efficient Chain-of-Thought LLMs
by: Du, Yanrui, et al.
Published: (2026)

Evaluating Large Language Models for Generalization and Robustness via Data Compression
by: Li, Yucheng, et al.
Published: (2024)

Debiasing CLIP: Interpreting and Correcting Bias in Attention Heads
by: Yeo, Wei Jie, et al.
Published: (2025)

CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model
by: Ma, Jingying, et al.
Published: (2025)