Evidence map›Paper›PMID 34809864›Full record

ArticlePET clinics2022

Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions).

Navid Hasani, Sriram S Paravastu, Faraz Farhadi, Fereshteh Yousefirizi, Michael A Morris, Arman Rahmim, Mark Roschewski, Ronald M Summers, Babak Saboury

Open access · greenAbstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in PET clinics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
7.3field-weighted citation impact, top 2% 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

15 citing papers in PubMed, 56 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Deep learning for [The Lancet. Digital health · 2024
    Article
  10. A whole-body diffusion MRI normal atlas: development, evaluation and initial use.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
    Article
  11. Article
  12. Review
  13. Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023
    Article
  14. Review
  15. 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

9 authors at 4 institutions in 2 countries.

Navid HasaniDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA; University of Queensland Faculty of Medicine, Ochsner Clinical School, New Orleans, LA 70121, USA.
Sriram S ParavastuDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA.
Faraz FarhadiDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA.
Fereshteh YousefiriziDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
Michael A MorrisDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland-Baltimore Country, Baltimore, MD, USA.
Arman RahmimDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada; Department of Radiology, BC Cancer Research Institute, University of British Columbia, 675 West 10th Avenue, Vancouver, British Columbia, V5Z 1L3, Canada.
Mark RoschewskiLymphoid Malignancies Branch, Center for Cancer Research, National Institutes of Health, Bethesda, MD, USA.
Ronald M SummersDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA. Electronic address: rsummers@mail.cc.nih.gov.
Babak SabouryDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 1C455, Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland-Baltimore Country, Baltimore, MD, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: babak.saboury@nih.gov.
National Institutes of Health Clinical Center · USNational Institutes of Health · USUniversity of British Columbia · CAUniversity of Maryland, Baltimore · US

Funding

Computer Aided Detection for Radiologic ImagesZIACL040004 · CLC · CLINICAL CENTER · PI SUMMERS, RONALD M. · 2009 to 2025
$0k
Intramural NIH HHS Z99 CL999999
6 · The paper itself

Abstract

Malignant lymphomas are a family of heterogenous disorders caused by clonal proliferation of lymphocytes.

Indexed as

Artificial IntelligenceLymphomaFluorodeoxyglucose F18HumansFluorodeoxyglucose F18Artificial intelligenceDeep learningDetectionLymphomaPositron emission tomography (PET)RadiomicsRadiophenomicsSegmentation

Identifiers

PMID34809864
PMCPMC8735853
OpenAlexW3217466224

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.