Evidence map›Paper›PMID 41781096›Full record

ReviewAcademic radiology2026

From Artificial Intelligence to Robotics: How to Navigate Technological Innovation in Radiology With the Gartner Hype Cycle.

Siddhant Dogra, Safiullah Rifai, Mohiuddin Hadi, Tarek Hanna, Anna Rozenshtein, Michele Retrouvey, Heng Huang, Florence X Doo

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Academic radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Siddhant DograDepartment of Radiology, New York University Langone Health, New York, New York (S.D.). Electronic address: Siddhant.Dogra@nyulangone.org.
Safiullah RifaiUniversity of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland (S.R., T.H., H.H., F.X.D.); University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, Maryland (S.R.). Electronic address: safiullah.rifai@som.umaryland.edu.
Mohiuddin HadiDepartment of Radiology, University of Louisville, Louisville, Kentucky (M.H.). Electronic address: mohiuddin.hadi@louisville.edu.
Tarek HannaUniversity of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland (S.R., T.H., H.H., F.X.D.). Electronic address: tarek.hanna@umm.edu.
Anna RozenshteinDepartment of Radiology, Westchester Medical Center, New York Medical College, Valhalla, New York (A.R.). Electronic address: anna.rozenshtein@wmchealth.org.
Michele RetrouveyDepartment of Women's and Children's Health, Florida Atlantic University Charles E. Schmidt College of Medicine, Boca Raton, Florida (M.R.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia Pennsylvania (M.R.). Electronic address: mretrouvey@health.fau.edu.
Heng HuangUniversity of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland (S.R., T.H., H.H., F.X.D.); University of Maryland Institute for Health Computing (UM-IHC), North Bethesda, Maryland (H.H., F.X.D.); Department of Computer Science, University of Maryland, College Park, Maryland (H.H.). Electronic address: heng@umd.edu.
Florence X DooUniversity of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland (S.R., T.H., H.H., F.X.D.); University of Maryland Institute for Health Computing (UM-IHC), North Bethesda, Maryland (H.H., F.X.D.). Electronic address: fdoo@som.umaryland.edu.

Funding

Understanding and addressing risks of low socioeconomic status and diabetes for heart failureP50MD017348 · NIMHD · JOHNS HOPKINS UNIVERSITY · PI IBE, CHIDINMA ADANNA · 2021 to 2025
$24.2M
CTSA K12 Program at Johns HopkinsK12TR004925 · NCATS · JOHNS HOPKINS UNIVERSITY · PI KHALIL G GHANEM · 2025 to 2026
$3.2M
NCATS NIH HHS K12 TR004925NIMHD NIH HHS P50 MD017348
6 · The paper itself

Abstract

Radiology is rapidly evolving across both technology and practice, making it difficult to distinguish innovations with genuine lasting impact from those that may fade after initial enthusiasm. In this narrative review, we use an expert-informed framework and a targeted appraisal of the literature to map key advances in radiology onto the Gartner hype cycle, across three key areas: software and algorithms, advanced imaging tools and techniques, and clinical practice paradigms. We provide strategic considerations for radiologists, trainees, and leaders, including potential future implications for the specialty. Together, radiologists, trainees, and leaders play distinct and complementary roles in guiding the adoption of emerging technologies, from deepening clinical-technical expertise to developing systemic governance and infrastructure that supports safe, evidence-driven implementation. As part 6 of the Radiology Research Alliance (RRA) review series on emerging technologies in collaboration with the University of Maryland Institute for Health Computing (UM-IHC) and the Medical Intelligent Imaging (UM2ii) Center, this paper provides a critical perspective on how radiologists, trainees, and leaders can navigate the hype cycle to identify meaningful innovations and guide strategic adoption in practice.

Indexed as

Artificial IntelligenceDiffusion of InnovationInventionsRadiologyRoboticsHumansAdvanced imaging techniquesArtificial intelligenceClinical practice paradigmsGartner hype cycleTechnology and innovation

Identifiers

PMID41781096
PMCPMC12965137

What Socratic 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 Socratic graph.