Search Results for author:
Found 9 papers, 1 papers with code
Semi-Supervised Learning from Small Annotated Data and Large Unlabeled Data for Fine-grained PICO Entity Recognition
Materials and Methods: Using a corpus of 2, 511 abstracts with PICO mentions from 4 public datasets, we developed a semi-supervised method to facilitate the training of a NER model, FinePICO, by combining limited annotated data of PICO entities and abundant unlabeled data.
A MapReduce Approach to Effectively Utilize Long Context Information in Retrieval Augmented Language Models
While holding great promise for improving and facilitating healthcare, large language models (LLMs) struggle to produce up-to-date responses on evolving topics due to outdated knowledge or hallucination.
Demystifying Large Language Models for Medicine: A Primer
We then review the strategies, such as prompt engineering and fine-tuning, to adapt standard LLMs to specialized medical tasks.
Closing the gap between open-source and commercial large language models for medical evidence summarization
Large language models (LLMs) hold great promise in summarizing medical evidence.
A Span-based Model for Extracting Overlapping PICO Entities from RCT Publications
On the PICO-Corpus, PICOX obtained higher recall and F1 scores than the baseline and improved the micro recall score from 56. 66 to 67. 33.
Leveraging Generative AI for Clinical Evidence Summarization Needs to Ensure Trustworthiness
Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence.
Efficient Learning for Selecting Top-m Context-Dependent Designs
We consider a simulation optimization problem for a context-dependent decision-making, which aims to determine the top-m designs for all contexts.
An Efficient Dynamic Sampling Policy For Monte Carlo Tree Search
We consider the popular tree-based search strategy within the framework of reinforcement learning, the Monte Carlo Tree Search (MCTS), in the context of finite-horizon Markov decision process.
