Evidence map›Paper›PMID 42769936›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2026

How Close Are We? Limitations and Progress of AI Models in Banff Lesion Scoring.

Yanfan Zhu, Juming Xiong, Ruining Deng, Yu Wang, Yaohong Wang, Shilin Zhao, Mengmeng Yin, Yuqing Liu, Haichun Yang, Yuankai Huo

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 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

10 authors.

Yanfan ZhuVanderbilt University, Nashville TN 37235, USA.
Juming XiongVanderbilt University, Nashville TN 37235, USA.
Ruining DengWeill Cornell Medicine, New York, NY 10021, USA.
Yu WangVanderbilt University Medical Center, Nashville TN 37232, USA.
Yaohong WangUT MD Anderson Cancer Center,TX 77030, USA.
Shilin ZhaoVanderbilt University Medical Center, Nashville TN 37232, USA.
Mengmeng YinVanderbilt University Medical Center, Nashville TN 37232, USA.
Yuqing LiuTongji University School of Medicine, Shanghai, 200092, China.
Haichun YangVanderbilt University Medical Center, Nashville TN 37232, USA.
Yuankai HuoVanderbilt University, Nashville TN 37235, USA.

Funding

Complementary ex vivo multimodal optical imaging and in vivo Raman spectroscopy to understand tissue dynamicsR01EB033385 · NIBIB · VANDERBILT UNIVERSITY · PI MAHADEVAN-JANSEN, ANITA, REESE, JOHN JEFFREY · 2022 to 2025
$2.6M
AI-empowered 3D Computer Vision and Image-Omics Integration for Digital Kidney HistopathologyR01DK135597 · NIDDK · VANDERBILT UNIVERSITY · PI Yuankai Huo · 2023 to 2026
$2.1M
Dual-wavelength endoscopic Raman probe for eosinophilic esophagitisR01DK132338 · NIDDK · VANDERBILT UNIVERSITY · PI MAHADEVAN-JANSEN, ANITA · 2022 to 2025
$1.7M
NIBIB NIH HHS R01 EB033385NIDDK NIH HHS R01 DK132338NIDDK NIH HHS R01 DK135597
6 · The paper itself

Abstract

The Banff Classification provides the global standard for evaluating renal transplant biopsies, yet its semi-quantitative nature, complex criteria, and inter-observer variability present significant challenges for computational replication. In this study, we explore the feasibility of approximating Banff lesion scores using existing deep learning models through a modular, rule-based framework. We decompose each Banff indicator-such as glomerulitis

Indexed as

Banff ClassificationDeep LearningKidney Transplant Pathology

Identifiers

PMID42769936
PMCPMC13591582

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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.