Cover Image

Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Klein, Omer Noy, Hüyük, Alihan, Shamir, Ron, Shalit, Uri, van der Schaar, Mihaela
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Experiment Design with Synthetic Controls
by: Hüyük, Alihan, et al.
Published: (2024)

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
by: Sun, Hao, et al.
Published: (2023)

Defining Expertise: Applications to Treatment Effect Estimation
by: Hüyük, Alihan, et al.
Published: (2024)

When is Off-Policy Evaluation (Reward Modeling) Useful in Contextual Bandits? A Data-Centric Perspective
by: Sun, Hao, et al.
Published: (2023)

Strategically Linked Decisions in Long-Term Planning and Reinforcement Learning
by: Hüyük, Alihan, et al.
Published: (2025)

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities
by: Sun, Hao, et al.
Published: (2025)

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies
by: Gutman, Rom, et al.
Published: (2025)

Towards Automated Knowledge Integration From Human-Interpretable Representations
by: Kobalczyk, Katarzyna, et al.
Published: (2024)

Deep Hierarchical Learning with Nested Subspace Networks for Large Language Models
by: Rauba, Paulius, et al.
Published: (2025)

No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs
by: Kacprzyk, Krzysztof, et al.
Published: (2025)

Set Valued Predictions For Robust Domain Generalization
by: Tsibulsky, Ron, et al.
Published: (2025)

Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
by: Benac, Leo, et al.
Published: (2026)

Disentangling Recognition and Decision Regrets in Image-Based Reinforcement Learning
by: Hüyük, Alihan, et al.
Published: (2024)

Not All Explanations for Deep Learning Phenomena Are Equally Valuable
by: Jeffares, Alan, et al.
Published: (2025)

Preference Learning for AI Alignment: a Causal Perspective
by: Kobalczyk, Katarzyna, et al.
Published: (2025)

Active Timepoint Selection for Learning Measure-Valued Trajectories
by: Huynh, Nicolas, et al.
Published: (2026)

Inverse-RLignment: Large Language Model Alignment from Demonstrations through Inverse Reinforcement Learning
by: Sun, Hao, et al.
Published: (2024)

Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers
by: Curth, Alicia, et al.
Published: (2024)

Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations
by: Kacprzyk, Krzysztof, et al.
Published: (2024)

Matchmaker: Self-Improving Large Language Model Programs for Schema Matching
by: Seedat, Nabeel, et al.
Published: (2024)

Simulating Viva Voce Examinations to Evaluate Clinical Reasoning in Large Language Models
by: Chiu, Christopher, et al.
Published: (2025)

Why Tabular Foundation Models Should Be a Research Priority
by: van Breugel, Boris, et al.
Published: (2024)

Machine Learning with Requirements: a Manifesto
by: Giunchiglia, Eleonora, et al.
Published: (2023)

Automatically Learning Hybrid Digital Twins of Dynamical Systems
by: Holt, Samuel, et al.
Published: (2024)

Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport
by: Amad, Harry, et al.
Published: (2026)

Automatic Construction of Clinical Scoring Systems with LLM Agents
by: Estévez, Silas Ruhrberg, et al.
Published: (2026)

Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments
by: Rauba, Paulius, et al.
Published: (2024)

LaTable: Towards Large Tabular Models
by: van Breugel, Boris, et al.
Published: (2024)

Discovery of Hidden Miscalibration Regimes
by: Kobalczyk, Katarzyna, et al.
Published: (2026)

Automated Ensemble Multimodal Machine Learning for Healthcare
by: Imrie, Fergus, et al.
Published: (2024)

Unlocking Historical Clinical Trial Data with ALIGN: A Compositional Large Language Model System for Medical Coding
by: Seedat, Nabeel, et al.
Published: (2024)

Language Bottleneck Models for Qualitative Knowledge State Modeling
by: Berthon, Antonin, et al.
Published: (2025)

On Error Propagation of Diffusion Models
by: Li, Yangming, et al.
Published: (2023)

Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond
by: Jeffares, Alan, et al.
Published: (2024)

A Study of Posterior Stability for Time-Series Latent Diffusion
by: Li, Yangming, et al.
Published: (2024)

Decision Tree Induction Through LLMs via Semantically-Aware Evolution
by: Liu, Tennison, et al.
Published: (2025)

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI
by: Seedat, Nabeel, et al.
Published: (2024)

Tiny Autoregressive Recursive Models
by: Rauba, Paulius, et al.
Published: (2026)

Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
by: Melnychuk, Valentyn, et al.
Published: (2024)

What's the next frontier for Data-centric AI? Data Savvy Agents
by: Seedat, Nabeel, et al.
Published: (2025)