Beyond Algorithms: Conceptual Innovation in Medical Imaging AI.

Mark A Anastasio

Abstract readPreprint

In one paragraph

Article in ArXiv, 2026. 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

1 author.

Mark A AnastasioMallinckrodt Institute of Radiology and Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63110 USA.

Funding

The Center for Label-free Imagingand Multiscale Biophotonics (CLIMB)P41EB031772 · NIBIB · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Stephen A Boppart · 2022 to 2026

$7.6M

Deep learning technologies for estimating the optimal task performance of medical imaging systemsR01EB034249 · NIBIB · WASHINGTON UNIVERSITY · PI Mark A Anastasio · 2023 to 2026

$1.7M

NIBIB NIH HHS P41 EB031772NIBIB NIH HHS R01 EB034249

6 · The paper itself

Abstract

Artificial intelligence has driven rapid progress in medical imaging research, producing increasingly sophisticated algorithms and steady improvements on benchmark tasks. However, this algorithm-centric trajectory has also revealed a growing imbalance: while computational methods advance rapidly, the conceptual foundations that define imaging tasks, evaluation metrics, and clinical meaning sometimes remain underexamined. In this Perspective, we distinguish

Indexed as

artificial intelligenceconceptual innovationevaluation methodologyMedical imagingtask definition

Identifiers

PMID42368256

PMCPMC13308450

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.