How Should We Represent History in Interpretable Models of Clinical Policies?
Fuente:
arXiv
Saved in:
| Main Authors: | Matsson, Anton, Stempfle, Lena, Rao, Yaochen, Margolin, Zachary R., Litman, Heather J., Johansson, Fredrik D. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Pragmatic Policy Development via Interpretable Behavior Cloning
by: Matsson, Anton, et al.
Published: (2025)
by: Matsson, Anton, et al.
Published: (2025)
Prediction Models That Learn to Avoid Missing Values
by: Stempfle, Lena, et al.
Published: (2025)
by: Stempfle, Lena, et al.
Published: (2025)
Unsupervised domain adaptation by learning using privileged information
by: Breitholtz, Adam, et al.
Published: (2023)
by: Breitholtz, Adam, et al.
Published: (2023)
Unlocking the Potential of Past Research: Using Generative AI to Reconstruct Healthcare Simulation Models
by: Monks, Thomas, et al.
Published: (2025)
by: Monks, Thomas, et al.
Published: (2025)
Propensity Score Matching: Should We Use It in Designing Observational Studies?
by: Wan, Fei
Published: (2024)
by: Wan, Fei
Published: (2024)
Linking Measures of Inbreeding and Genetic Load to Demographic Histories Across Three Species of Bears
by: Heather R. Clendenin, et al.
Published: (2025)
by: Heather R. Clendenin, et al.
Published: (2025)
Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series
by: Brown, Zachary C., et al.
Published: (2025)
by: Brown, Zachary C., et al.
Published: (2025)
On the Mechanistic Interpretability of Neural Networks for Causality in Bio-statistics
by: Conan, Jean-Baptiste A.
Published: (2025)
by: Conan, Jean-Baptiste A.
Published: (2025)
Transfer Learning Between U.S. Presidential Elections: How Should We Learn From A 2020 Ad Campaign To Inform 2024 Ad Campaigns?
by: Miao, Xinran, et al.
Published: (2024)
by: Miao, Xinran, et al.
Published: (2024)
PISA: An AI Pipeline for Interpretable-by-design Survival Analysis Providing Multiple Complexity-Accuracy Trade-off Models
by: Schlender, Thalea, et al.
Published: (2025)
by: Schlender, Thalea, et al.
Published: (2025)
How Generalizable Is My Behavior Cloning Policy? A Statistical Approach to Trustworthy Performance Evaluation
by: Vincent, Joseph A., et al.
Published: (2024)
by: Vincent, Joseph A., et al.
Published: (2024)
Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight
by: Ye, Junze, et al.
Published: (2025)
by: Ye, Junze, et al.
Published: (2025)
Interpreting Net Survival: What We Estimate Versus What We Think We Estimate
by: Smith, Matthew J.
Published: (2026)
by: Smith, Matthew J.
Published: (2026)
Fairness-Aware and Interpretable Policy Learning
by: Bearth, Nora, et al.
Published: (2025)
by: Bearth, Nora, et al.
Published: (2025)
Detecting Structural Heart Disease from Electrocardiograms via a Generalized Additive Model of Interpretable Foundation-Model Predictors
by: Zhou, Ya, et al.
Published: (2026)
by: Zhou, Ya, et al.
Published: (2026)
Improving Policy-Oriented Agent-Based Modeling with History Matching: A Case Study
by: O'Gara, David, et al.
Published: (2024)
by: O'Gara, David, et al.
Published: (2024)
Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis
by: Zhao, Yao, et al.
Published: (2026)
by: Zhao, Yao, et al.
Published: (2026)
Enhancing Data Efficiency and Feature Identification for Lithium-Ion Battery Lifespan Prediction by Deciphering Interpretation of Temporal Patterns and Cyclic Variability Using Attention-Based Models
by: Lee, Jaewook, et al.
Published: (2023)
by: Lee, Jaewook, et al.
Published: (2023)
Predicting ICU Readmission in Acute Pancreatitis Patients Using a Machine Learning-Based Model with Enhanced Clinical Interpretability
by: Chen, Shuheng, et al.
Published: (2025)
by: Chen, Shuheng, et al.
Published: (2025)
Learning Explainable Treatment Policies with Clinician-Informed Representations: A Practical Approach
by: Ferstad, Johannes O., et al.
Published: (2024)
by: Ferstad, Johannes O., et al.
Published: (2024)
Decade-long Emission Forecasting with an Ensemble Model in Taiwan
by: Hung, Gordon, et al.
Published: (2025)
by: Hung, Gordon, et al.
Published: (2025)
Performance Evaluation of Large Language Models in Statistical Programming
by: Song, Xinyi, et al.
Published: (2025)
by: Song, Xinyi, et al.
Published: (2025)
Investigating Mode Effects in Interviewer Variances Using Two Representative Multi-mode Surveys
by: Yu, Wenshan, et al.
Published: (2024)
by: Yu, Wenshan, et al.
Published: (2024)
Subnational Geocoding of Global Disasters Using Large Language Models
by: Ronco, Michele, et al.
Published: (2025)
by: Ronco, Michele, et al.
Published: (2025)
Data-Driven Bayesian Network Models of Hurricane Evacuation Decision Making
by: Wang, Hui Sophie, et al.
Published: (2023)
by: Wang, Hui Sophie, et al.
Published: (2023)
An Accurate and Interpretable Framework for Trustworthy Process Monitoring
by: Wang, Hao, et al.
Published: (2023)
by: Wang, Hao, et al.
Published: (2023)
StatLLM: A Dataset for Evaluating the Performance of Large Language Models in Statistical Analysis
by: Song, Xinyi, et al.
Published: (2025)
by: Song, Xinyi, et al.
Published: (2025)
HiBayES: A Hierarchical Bayesian Modeling Framework for AI Evaluation Statistics
by: Luettgau, Lennart, et al.
Published: (2025)
by: Luettgau, Lennart, et al.
Published: (2025)
TCKAN:A Novel Integrated Network Model for Predicting Mortality Risk in Sepsis Patients
by: Dong, Fanglin
Published: (2024)
by: Dong, Fanglin
Published: (2024)
Evaluating the Use of Large Language Models as Synthetic Social Agents in Social Science Research
by: Madden, Emma Rose
Published: (2025)
by: Madden, Emma Rose
Published: (2025)
DeepScore: A Comprehensive Approach to Measuring Quality in AI-Generated Clinical Documentation
by: Oleson, Jon
Published: (2024)
by: Oleson, Jon
Published: (2024)
A Regression Mixture Model to understand the effect of the Covid-19 pandemic on Public Transport Ridership
by: Moreau, Hugues, et al.
Published: (2024)
by: Moreau, Hugues, et al.
Published: (2024)
From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models
by: Zhang, Jiaxin, et al.
Published: (2026)
by: Zhang, Jiaxin, et al.
Published: (2026)
AI for Handball: predicting and explaining the 2024 Olympic Games tournament with Deep Learning and Large Language Models
by: Felice, Florian
Published: (2024)
by: Felice, Florian
Published: (2024)
RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning
by: Jin, Congyun, et al.
Published: (2024)
by: Jin, Congyun, et al.
Published: (2024)
Should the Olympic sprint skaters run the 500 meter twice?
by: Hjort, Nils Lid
Published: (2026)
by: Hjort, Nils Lid
Published: (2026)
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots
by: Xin, Xi, et al.
Published: (2024)
by: Xin, Xi, et al.
Published: (2024)
Classification Modeling with RNN-Based, Random Forest, and XGBoost for Imbalanced Data: A Case of Early Crash Detection in ASEAN-5 Stock Markets
by: Siswara, Deri, et al.
Published: (2024)
by: Siswara, Deri, et al.
Published: (2024)
Beyond Words: How Large Language Models Perform in Quantitative Management Problem-Solving
by: Kuzmanko, Jonathan
Published: (2025)
by: Kuzmanko, Jonathan
Published: (2025)
A Dynamic Dirichlet Process Mixture Model for the Partisan Realignment of Civil Rights Issues in the U.S. House of Representatives
by: Xiang, Nuannuan, et al.
Published: (2025)
by: Xiang, Nuannuan, et al.
Published: (2025)
Similar Items
-
Pragmatic Policy Development via Interpretable Behavior Cloning
by: Matsson, Anton, et al.
Published: (2025) -
Prediction Models That Learn to Avoid Missing Values
by: Stempfle, Lena, et al.
Published: (2025) -
Unsupervised domain adaptation by learning using privileged information
by: Breitholtz, Adam, et al.
Published: (2023) -
Unlocking the Potential of Past Research: Using Generative AI to Reconstruct Healthcare Simulation Models
by: Monks, Thomas, et al.
Published: (2025) -
Propensity Score Matching: Should We Use It in Designing Observational Studies?
by: Wan, Fei
Published: (2024)