PICO

16 papers with code • 1 benchmarks • 0 datasets

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Most implemented papers

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

nenadmarkus/pico 20 May 2013

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

devkotasabin/EBM-NLP ACL 2018

We present a corpus of 5, 000 richly annotated abstracts of medical articles describing clinical randomized controlled trials.

PICO Element Detection in Medical Text via Long Short-Term Memory Neural Networks

jind11/PubMed-PICO-Detection WS 2018

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

gauravsc/pico-tagging 21 Oct 2019

The network is then fine-tuned on a combination of real and these newly constructed artificial labeled instances.

Computing High Accuracy Power Spectra with Pico

marius311/pypico 2 Dec 2007

This paper presents the second release of Pico (Parameters for the Impatient COsmologist).

Machine Learning in Downlink Coordinated Multipoint in Heterogeneous Networks

farismismar/DL-CoMP-Machine-Learning 30 Aug 2016

We propose a method for downlink coordinated multipoint (DL CoMP) in heterogeneous fifth generation New Radio (NR) networks.

Advancing PICO Element Detection in Biomedical Text via Deep Neural Networks

jind11/Deep-PICO-Detection 30 Oct 2018

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.

Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks

L-ENA/HealthINF2020 30 Jan 2020

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.

Predicting Clinical Trial Results by Implicit Evidence Integration

Alibaba-NLP/EBM-Net EMNLP 2020

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.

Sent2Span: Span Detection for PICO Extraction in the Biomedical Text without Span Annotations

evidence-surveillance/sent2span Findings (EMNLP) 2021

The rapid growth in published clinical trials makes it difficult to maintain up-to-date systematic reviews, which requires finding all relevant trials.