Copertina

Multimodal Clinical Trial Outcome Prediction with Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zheng, Wenhao, Wang, Liaoyaqi, Peng, Dongshen, Xu, Hongxia, Li, Yun, Zhu, Hongtu, Fu, Tianfan, Yao, Huaxiu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization
di: Zhu, Kangyu, et al.
Pubblicazione: (2024)

TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models
di: Yue, Ling, et al.
Pubblicazione: (2024)

TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model
di: Wang, Yue, et al.
Pubblicazione: (2024)

ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning
di: Yue, Ling, et al.
Pubblicazione: (2024)

RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
di: Xia, Peng, et al.
Pubblicazione: (2024)

Language Interaction Network for Clinical Trial Approval Estimation
di: Gao, Chufan, et al.
Pubblicazione: (2024)

MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
di: Xia, Peng, et al.
Pubblicazione: (2024)

CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing
di: Zheng, Wenhao, et al.
Pubblicazione: (2025)

Uncertainty Quantification on Clinical Trial Outcome Prediction
di: Chen, Tianyi, et al.
Pubblicazione: (2024)

Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification
di: Kang, Haoqiang, et al.
Pubblicazione: (2023)

Breach in the Shield: Unveiling the Vulnerabilities of Large Language Models
di: Dai, Runpeng, et al.
Pubblicazione: (2025)

MEIT: Multimodal Electrocardiogram Instruction Tuning on Large Language Models for Report Generation
di: Wan, Zhongwei, et al.
Pubblicazione: (2024)

Retrieval-Reasoning Large Language Model-based Synthetic Clinical Trial Generation
di: Xu, Zerui, et al.
Pubblicazione: (2024)

Making Pre-trained Language Models Great on Tabular Prediction
di: Yan, Jiahuan, et al.
Pubblicazione: (2024)

MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning
di: Xia, Peng, et al.
Pubblicazione: (2025)

MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
di: Xia, Peng, et al.
Pubblicazione: (2024)

MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding
di: Han, Siwei, et al.
Pubblicazione: (2025)

DrugAgent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction
di: Inoue, Yoshitaka, et al.
Pubblicazione: (2024)

From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction
di: Zhu, Mingcheng, et al.
Pubblicazione: (2026)

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
di: Zhou, Yiyang, et al.
Pubblicazione: (2024)

FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
di: Nie, Fan, et al.
Pubblicazione: (2024)

Process Supervision of Confidence Margin for Calibrated LLM Reasoning
di: Wang, Liaoyaqi, et al.
Pubblicazione: (2026)

Always Tell Me The Odds: Fine-grained Conditional Probability Estimation
di: Wang, Liaoyaqi, et al.
Pubblicazione: (2025)

HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model
di: Guo, Haiyang, et al.
Pubblicazione: (2025)

TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction
di: Yue, Ling, et al.
Pubblicazione: (2024)

CPLLM: Clinical Prediction with Large Language Models
di: Shoham, Ofir Ben, et al.
Pubblicazione: (2023)

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
di: Dai, Runpeng, et al.
Pubblicazione: (2025)

ChemMLLM: Chemical Multimodal Large Language Model
di: Tan, Qian, et al.
Pubblicazione: (2025)

Benchmarking Large Language Model Uncertainty for Prompt Optimization
di: Guo, Pei-Fu, et al.
Pubblicazione: (2024)

DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models
di: Gao, Shangqian, et al.
Pubblicazione: (2024)

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
di: Xia, Peng, et al.
Pubblicazione: (2024)

CREAM: Consistency Regularized Self-Rewarding Language Models
di: Wang, Zhaoyang, et al.
Pubblicazione: (2024)

Automatically Labeling Clinical Trial Outcomes: A Large-Scale Benchmark for Drug Development
di: Gao, Chufan, et al.
Pubblicazione: (2024)

Training Large Language Models to Predict Clinical Events
di: Turtel, Benjamin, et al.
Pubblicazione: (2026)

Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences
di: Wang, Xiyao, et al.
Pubblicazione: (2024)

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
di: Zhou, Yiyang, et al.
Pubblicazione: (2023)

ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks
di: Zhu, Yinghao, et al.
Pubblicazione: (2024)

Are Large Language Models Table-based Fact-Checkers?
di: Zhang, Hanwen, et al.
Pubblicazione: (2024)

Benchmarking the Thinking Mode of Multimodal Large Language Models in Clinical Tasks
di: Hong, Jindong, et al.
Pubblicazione: (2025)

ctELM: Decoding and Manipulating Embeddings of Clinical Trials with Embedding Language Models
di: Ondov, Brian, et al.
Pubblicazione: (2026)