Evidence map›Paper›PMID 38516034›Full record

ArticleProceedings. IEEE International Conference on Healthcare Informatics2023

An End-to-end

Ko-Hong Lin, Jay-Jiguang Zhu, Judith A Smith, Yejin Kim, Xiaoqian Jiang

Abstract read
In one paragraph

Article in Proceedings. IEEE International Conference on Healthcare Informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ko-Hong LinSchool of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Jay-Jiguang ZhuMcGovern Medical School, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Judith A SmithMcGovern Medical School, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Yejin KimSchool of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Xiaoqian JiangSchool of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.

Funding

Open Health Natural Language Processing CollaboratoryU01TR002062 · NCATS · MAYO CLINIC ROCHESTER · PI JIANG, XIAOQIAN, LIU, HONGFANG · 2017 to 2021
$7.6M
Finding Combinatorial Drug Repositioning Therapy For Alzheimer'S Disease And Related DementiasR01AG066749 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI JIANG, XIAOQIAN, ZHENG, WENJIN JIM · 2020 to 2024
$4.4M
Decentralized differentially-private methods for dynamic data release and analysisR01LM013712 · NLM · YALE UNIVERSITY · PI JIANG, XIAOQIAN, OHNO-MACHADO, LUCILA · 2022 to 2025
$2.5M
NCATS NIH HHS U01 TR002062NIA NIH HHS R01 AG066749NLM NIH HHS R01 LM013712
6 · The paper itself

Abstract

Our study aims to address the challenges in drug development for glioblastoma, a highly aggressive brain cancer with poor prognosis. We propose a computational framework that utilizes machine learning-based propensity score matching to estimate counterfactual treatment effects and predict synergistic effects of drug combinations. Through our

Indexed as

end-to-end pipelineglioblastomain-vitro validationpropensity score matching

Identifiers

PMID38516034
PMCPMC10956733

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.