Evidence map›Paper›PMID 37116913›Full record

ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2023

Artificial Intelligence Algorithms Need to Be Explainable-or Do They?

Tyler J Bradshaw, Melissa D McCradden, Abhinav K Jha, Joyita Dutta, Babak Saboury, Eliot L Siegel, Arman Rahmim

Abstract read
In one paragraph

Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Should end-to-end deep learning replace handcrafted radiomics?European journal of nuclear medicine and molecular imaging · 2025
    Article
  4. Review
  5. Article
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

7 authors.

Tyler J BradshawUniversity of Wisconsin-Madison, Madison, Wisconsin; tbradshaw@wisc.edu.
Melissa D McCraddenHospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Abhinav K JhaWashington University in St. Louis, St. Louis, Missouri.
Joyita DuttaUniversity of Massachusetts Amherst, Amherst, Massachusetts.
Babak SabouryNational Institutes of Health, Bethesda, Maryland.
Eliot L SiegelUniversity of Maryland School of Medicine, Baltimore, Maryland; and.
Arman RahmimUniversity of British Columbia, Vancouver, British Columbia, Canada.

Funding

Longitudinal predictive modeling for tau in Alzheimer's diseaseR01AG072669 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI DUTTA, JOYITA · 2021 to 2025
$2.7M
Super-Resolution Tau PET Imaging for Alzheimer's DiseaseR03AG070750 · NIA · UNIVERSITY OF MASSACHUSETTS LOWELL · PI DUTTA, JOYITA · 2021 to 2022
$304k
NIA NIH HHS R01 AG072669NIA NIH HHS R03 AG070750
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

AlgorithmsArtificial Intelligence

Identifiers

PMID37116913
PMCPMC10885777

What OpenQuestion holds

Textmetadata
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.