Browse State-of-the-Art › PICO
PICO
26 papers with code · 1 benchmark · 0 datasets archive 2025-07-28
The proliferation of healthcare data has contributed to the widespread usage of the PICO paradigm for creating specific clinical questions from RCT.
PICO is a mnemonic that stands for:
Population/Problem: Addresses the characteristics of populations involved and the specific characteristics of the disease or disorder. Intervention: Addresses the primary intervention (including treatments, procedures, or diagnostic tests) along with any risk factors. Comparison: Compares the efficacy of any new interventions with the primary intervention. Outcome: Measures the results of the intervention, including improvements or side effects. PICO is an essential tool that aids evidence-based practitioners in creating precise clinical questions and searchable keywords to address those issues. It calls for a high level of technical competence and medical domain knowledge, but it’s also frequently very time-consuming.
Automatically identifying PICO elements from this large sea of data can be made easier with the aid of machine learning (ML) and natural language processing (NLP). This facilitates the development of precise research questions by evidence-based practitioners more quickly and precisely.
Empirical studies have shown that the use of PICO frames improves the specificity and conceptual clarity of clinical problems, elicits more information during pre-search reference interviews, leads to more complex search strategies, and yields more precise search results.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| EBM PICO (3 rows) | BioLinkBERT (large) | LinkBERT: Pretraining Language Models with Document Links | code | Syntology ran 0 of 14 samples · 14 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
No dataset record in the archive lists this task.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
26 shown of 26 papers with code (68 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
20 May 2013 8 repositories listedWe describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors.
-
31 Jul 2020 2 repositories listedIn this paper, we challenge this assumption by showing that for domains with abundant unlabeled text, such as biomedicine, pretraining language models from scratch results in substantial gains over continual pretraining…
-
21 Oct 2019 2 repositories listedThe network is then fine-tuned on a combination of real and these newly constructed artificial labeled instances.
-
1 Jul 2018 2 repositories listedSuccessful evidence-based medicine (EBM) applications rely on answering clinical questions by analyzing large medical literature databases.
-
11 Jun 2018 2 repositories listedWe present a corpus of 5, 000 richly annotated abstracts of medical articles describing clinical randomized controlled trials.
-
15 Sep 2024 1 repository listedIn recent years, there has been a surge in the publication of clinical trial reports, making it challenging to conduct systematic reviews.
-
18 Feb 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverifiedBut how factual are these summaries in a high-stakes domain like medicine?
-
2 Feb 2024 1 repository listed Syntology ran 9 of 14 samples · 5 unverified · 14 pointer-only (licence)Existing large language models (LLMs) evaluation methods typically focus on testing the performance on some closed-environment and domain-specific benchmarks with human annotations.
-
12 Aug 2023 1 repository listedMedical systematic reviews can be very costly and resource intensive.
-
10 May 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverifiedUnder partial-label learning (PLL) where, for each training instance, only a set of ambiguous candidate labels containing the unknown true label is accessible, contrastive learning has recently boosted the performance…
-
2 Mar 2023 1 repository listedPico-nanophytoplankton organisms are dominant in oceanic oligotrophic areas but their adaptive growth rates make their contribution to the carbon cycle difficult to estimate.
-
7 Oct 2022 1 repository listedOur approach accurately generates realistic depth images in a wide range of scenarios, allowing the performance of an optical depth imaging system to be established without the need for costly and laborious field…
-
19 Jul 2022 1 repository listedBiomedical text summarization is a critical task for comprehension of an ever-growing amount of biomedical literature.
-
1 May 2022 1 repository listedTo break through the bottleneck, we propose DISTANT-CTO, a novel distantly supervised PICO entity extraction approach using the clinical trials literature, to generate a massive weakly-labeled dataset with more than a…
-
29 Mar 2022 1 repository listed Syntology ran 0 of 14 samples · 14 unverifiedLanguage model (LM) pretraining can learn various knowledge from text corpora, helping downstream tasks.
-
2 Mar 2022 1 repository listedThis article introduces a neural network based on-device learning (ODL) approach to address this issue by retraining in deployed environments.
-
8 Feb 2022 1 repository listedThe learning-based, fully decentralized framework has been introduced to alleviate real-time problems and simultaneously pursue optimal planning policy.
-
22 Jan 2022 1 repository listed Syntology ran 2 of 2 samples · 0 unverifiedPartial label learning (PLL) is an important problem that allows each training example to be labeled with a coarse candidate set, which well suits many real-world data annotation scenarios with label ambiguity.
-
29 Sep 2021 1 repository listedPartial label learning (PLL) is an important problem that allows each training example to be labeled with a coarse candidate set, which well suits many real-world data annotation scenarios with label ambiguity.
-
9 Sep 2021 1 repository listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)The proposed Aggregation method for Sequential Labels from Crowds (AggSLC) jointly considers the characteristics of sequential labeling tasks, workers' reliabilities, and advanced machine learning techniques.
-
6 Sep 2021 1 repository listedThe rapid growth in published clinical trials makes it difficult to maintain up-to-date systematic reviews, which requires finding all relevant trials.
-
12 Oct 2020 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)In the CTRP framework, a model takes a PICO-formatted clinical trial proposal with its background as input and predicts the result, i.
-
30 Jan 2020 1 repository listedThis 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…
-
30 Oct 2018 1 repository listedOne is the PubMed-PICO dataset, where our best results outperform the previous best by 5.
-
30 Aug 2016 1 repository listedWe propose a method for downlink coordinated multipoint (DL CoMP) in heterogeneous fifth generation New Radio (NR) networks.
-
2 Dec 2007 1 repository listedThis paper presents the second release of Pico (Parameters for the Impatient COsmologist).
Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections