Evidence map›Paper›PMID 37963396›Full record

ArticleJournal of neural engineering2023

Novel machine learning approaches for improving the reproducibility and reliability of functional and effective connectivity from functional MRI.

Cooper J Mellema, Albert A Montillo

Open access · hybridAbstract read
In one paragraph

Article in Journal of neural engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 35% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
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

2 authors at 1 institution in 1 country.

Cooper J MellemaLyda Hill Department of Bioinformatics, Dallas, TX, United States of America.ORCID 0000-0001-8401-8889
Albert A MontilloLyda Hill Department of Bioinformatics, Dallas, TX, United States of America.ORCID 0000-0002-4353-290X
Lyda Hill Philanthropies · US

Funding

Quantitative Non-Contrast Perfusion using Arterial Spin Labeling for Assessment of Cancer Therapy ResponseU01CA207091 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI MADHURANTHAKAM, ANANTH J, MALDJIAN, JOSEPH A · 2017 to 2022
$3.1M
Correcting biases in deep learning modelsR01GM144486 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI Albert Amos Montillo · 2023 to 2026
$1.4M
Blood Biomarker for Alzheimer's Disease: PhospholipidsRF1AG059288 · NIA · UT SOUTHWESTERN MEDICAL CENTER · PI GERMAN, DWIGHT C., MCDONALD, JEFF G · 2019 to 2019
$1.2M
Predicting Parkinson's Disease Progression Rate Using Causal Measures of Functional MRI with Deep Learning Predictive ModelsF31NS115348 · NINDS · UT SOUTHWESTERN MEDICAL CENTER · PI MELLEMA, COOPER JAMES · 2019 to 2021
$104k
NCI NIH HHS U01 CA207091NIA NIH HHS RF1 AG059288NIGMS NIH HHS R01 GM144486NINDS NIH HHS F31 NS115348
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

BrainConnectomeHumansMachine LearningMagnetic Resonance ImagingReproducibility of Resultscausalityconnectivityeffective connectivityfMRIfunctional connectivityreliabilityreproducibility

Identifiers

PMID37963396
PMCPMC11583961
OpenAlexW4388661973

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.