Cover Image

Explainable AI for Clinical Outcome Prediction: A Survey of Clinician Perceptions and Preferences

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hou, Jun, Wang, Lucy Lu
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GAPS: A Clinically Grounded, Automated Benchmark for Evaluating AI Clinicians
by: Chen, Xiuyuan, et al.
Published: (2025)

MedArena: Comparing LLMs for Medicine-in-the-Wild Clinician Preferences
by: Wu, Eric, et al.
Published: (2026)

Towards Transparent AI: A Survey on Explainable Language Models
by: Palikhe, Avash, et al.
Published: (2025)

LLMs for Explainable AI: A Comprehensive Survey
by: Bilal, Ahsan, et al.
Published: (2025)

Towards Explainability in Legal Outcome Prediction Models
by: Valvoda, Josef, et al.
Published: (2024)

Multi-Domain Explainability of Preferences
by: Calderon, Nitay, et al.
Published: (2025)

Towards Transparent AI: A Survey on Explainable Large Language Models
by: Palikhe, Avash, et al.
Published: (2025)

TrendFact: A Benchmark for Explainable Hotspot Perception in Fact-Checking with Natural Language Explanation
by: Zhang, Xiaocheng, et al.
Published: (2024)

Emulating Clinician Cognition via Self-Evolving Deep Clinical Research
by: Ren, Ruiyang, et al.
Published: (2026)

Finding Words Associated with DIF: Predicting Differential Item Functioning using LLMs and Explainable AI
by: Maeda, Hotaka, et al.
Published: (2025)

A Survey of Explainable Knowledge Tracing
by: Bai, Yanhong, et al.
Published: (2024)

CHiRPE: A Step Towards Real-World Clinical NLP with Clinician-Oriented Model Explanations
by: Fong, Stephanie, et al.
Published: (2026)

From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
by: Zheng, Qirui, 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)

Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models
by: Chen, Zizhang, et al.
Published: (2024)

Towards Safe AI Clinicians: A Comprehensive Study on Large Language Model Jailbreaking in Healthcare
by: Zhang, Hang, et al.
Published: (2025)

Generative AI Perceptions: A Survey to Measure the Perceptions of Faculty, Staff, and Students on Generative AI Tools in Academia
by: Amani, Sara, et al.
Published: (2023)

Multimodal Clinical Trial Outcome Prediction with Large Language Models
by: Zheng, Wenhao, et al.
Published: (2024)

Know Your Limits: A Survey of Abstention in Large Language Models
by: Wen, Bingbing, et al.
Published: (2024)

Towards Explainable Multimodal Depression Recognition for Clinical Interviews
by: Zheng, Wenjie, et al.
Published: (2025)

A Comprehensive Survey on the Trustworthiness of Large Language Models in Healthcare
by: Aljohani, Manar, et al.
Published: (2025)

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy
by: Afzoon, Saleh, et al.
Published: (2025)

Explainability in Practice: A Survey of Explainable NLP Across Various Domains
by: Mohammadi, Hadi, et al.
Published: (2025)

AlignSurvey: A Comprehensive Benchmark for Human Preferences Alignment in Social Surveys
by: Lin, Chenxi, et al.
Published: (2025)

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey
by: Dang, Yunkai, et al.
Published: (2024)

CliniBench: A Clinical Outcome Prediction Benchmark for Generative and Encoder-Based Language Models
by: Grundmann, Paul, et al.
Published: (2025)

Understanding Public Perception of Crime in Bangladesh: A Transformer-Based Approach with Explainability
by: Hassan, Fatema Binte, et al.
Published: (2025)

EvidenceOutcomes: a Dataset of Clinical Trial Publications with Clinically Meaningful Outcomes
by: Zhou, Yiliang, et al.
Published: (2025)

Towards a Unified View of Preference Learning for Large Language Models: A Survey
by: Gao, Bofei, et al.
Published: (2024)

Generative AI in Saudi Arabia: A National Survey of Adoption, Risks, and Public Perceptions
by: AlDakheel, Abdulaziz, et al.
Published: (2026)

A Survey of the State of Explainable AI for Natural Language Processing
by: Danilevsky, Marina, et al.
Published: (2020)

A Survey on Human Preference Learning for Large Language Models
by: Jiang, Ruili, et al.
Published: (2024)

Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability
by: Shu, Dong, et al.
Published: (2025)

A Survey on Personalized and Pluralistic Preference Alignment in Large Language Models
by: Xie, Zhouhang, et al.
Published: (2025)

Robust Preference Optimization via Dynamic Target Margins
by: Sun, Jie, et al.
Published: (2025)

Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol
by: Zahidy, Misk Al, et al.
Published: (2025)

CQA-Eval: Designing Reliable Evaluations of Multi-paragraph Clinical QA under Resource Constraints
by: Bologna, Federica, et al.
Published: (2025)

Evaluating and Steering Modality Preferences in Multimodal Large Language Model
by: Zhang, Yu, et al.
Published: (2025)

Case-Specific Rubrics for Clinical AI Evaluation: Methodology, Validation, and LLM-Clinician Agreement Across 823 Encounters
by: Shah, Aaryan, et al.
Published: (2026)

AI Safety in Generative AI Large Language Models: A Survey
by: Chua, Jaymari, et al.
Published: (2024)