16 papers with code • 1 benchmarks • 0 datasets
We describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors.
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature
We present a corpus of 5, 000 richly annotated abstracts of medical articles describing clinical randomized controlled trials.
Successful evidence-based medicine (EBM) applications rely on answering clinical questions by analyzing large medical literature databases.
Constructing Artificial Data for Fine-tuning for Low-Resource Biomedical Text Tagging with Applications in PICO Annotation
The network is then fine-tuned on a combination of real and these newly constructed artificial labeled instances.
We propose a method for downlink coordinated multipoint (DL CoMP) in heterogeneous fifth generation New Radio (NR) networks.
One is the PubMed-PICO dataset, where our best results outperform the previous best by 5. 5%, 7. 9%, and 5. 8% for P, I, and O elements in terms of F1 score, respectively.
This paper contributes to solving problems related to ambiguity in PICO sentence prediction tasks, as well as highlighting how annotations for training named entity recognition systems are used to train a high-performing, but nevertheless flexible architecture for question answering in systematic review automation.
In the CTRP framework, a model takes a PICO-formatted clinical trial proposal with its background as input and predicts the result, i. e. how the Intervention group compares with the Comparison group in terms of the measured Outcome in the studied Population.
The rapid growth in published clinical trials makes it difficult to maintain up-to-date systematic reviews, which requires finding all relevant trials.