Mask of truth: model sensitivity to unexpected regions of medical images | Paper Citation Record

Observation 545ad308-9221-4ced-8ea9-7d32b6cb90d6 · outbound

This paper cites Characterizing the clinical adoption of medical ai devices through u.s.

Mask of truth: model sensitivity to unexpected regions of medical images Characterizing the clinical adoption of medical ai devices through u.s

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.458288Z

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Observation 29c39b9f-98b0-4e3f-b9ef-a8f265601f5b · outbound

This paper cites Artificial intelligence versus clinicians in disease diagnosis: systematic review.JMIR medical informatics, 7(3):e10010, 2019.

Mask of truth: model sensitivity to unexpected regions of medical images Artificial intelligence versus clinicians in disease diagnosis: systematic review.JMIR medical informatics, 7(3):e10010, 2019

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.449617Z

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Observation ba9eef18-3d16-452c-b16d-10e845aab2d9 · outbound

This paper cites Autonomous chest radiograph reporting using ai: estimation of clinical impact.

Mask of truth: model sensitivity to unexpected regions of medical images Autonomous chest radiograph reporting using ai: estimation of clinical impact

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.443226Z

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Observation ec6666b9-5d40-4000-bab7-0418f351457a · outbound

This paper cites Ho, and James Zou.

Mask of truth: model sensitivity to unexpected regions of medical images Ho, and James Zou

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.435781Z

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Observation 6187929e-c675-4736-9e41-f16b5b96e7fe · outbound

This paper cites Detecting shortcuts in medical images-a case study in chest x-rays.

Mask of truth: model sensitivity to unexpected regions of medical images Detecting shortcuts in medical images-a case study in chest x-rays

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.429117Z

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Observation 98b6e9c1-03b1-480b-971a-a49f570d6a3a · outbound

This paper cites Hidden stratification causes clinically meaningful failures in machine learning for medical imaging.

Mask of truth: model sensitivity to unexpected regions of medical images Hidden stratification causes clinically meaningful failures in machine learning for medical imaging

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.420375Z

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Observation 1b6da36e-01dc-46f1-8d95-a2a591c01a5a · outbound

This paper cites Counterfactual contrastive learning: robust representations via causal image synthesis.

Mask of truth: model sensitivity to unexpected regions of medical images Counterfactual contrastive learning: robust representations via causal image synthesis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.409921Z

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Observation d1e5361e-1f55-44ac-b30f-246e15402168 · outbound

This paper cites All you need is a guiding hand: Mitigating short- cut bias in deep learning models for medical imaging.

Mask of truth: model sensitivity to unexpected regions of medical images All you need is a guiding hand: Mitigating short- cut bias in deep learning models for medical imaging

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.402143Z

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Observation 4b80b51d-908c-4771-b744-c1480293cdfd · outbound

This paper cites Deep learning for understanding multilabel imbalanced chest x-ray datasets.

Mask of truth: model sensitivity to unexpected regions of medical images Deep learning for understanding multilabel imbalanced chest x-ray datasets

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.394234Z

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Observation fc461182-c07b-465e-9638-8800947cb678 · outbound

This paper cites Airogs: artificial intelligence for robust glaucoma screening chal- lenge.

Mask of truth: model sensitivity to unexpected regions of medical images Airogs: artificial intelligence for robust glaucoma screening chal- lenge

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.384941Z

Source-reported events for the cited work

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Observation 68c134c0-4f00-4721-96d8-3cd5bb608c32 · outbound

This paper cites Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review.Diagnostics, 11(8):1390, 2021.

Mask of truth: model sensitivity to unexpected regions of medical images Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review.Diagnostics, 11(8):1390, 2021

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.378019Z

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Observation c72b7881-e2f4-43ca-80e5-5e16903b41a2 · outbound

This paper cites Dynamic routing between capsules.

Mask of truth: model sensitivity to unexpected regions of medical images Dynamic routing between capsules

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.733698Z

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Observation ae84f1c5-66c6-43e5-9c64-b99efb2633dc · outbound

This paper cites Capsule networks against medical imaging data challenges.

Mask of truth: model sensitivity to unexpected regions of medical images Capsule networks against medical imaging data challenges

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.367603Z

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Observation 72623573-76d4-48aa-b1d5-27426ef2d558 · outbound

This paper cites A capsule network-based for identification of glaucoma in retinal images.

Mask of truth: model sensitivity to unexpected regions of medical images A capsule network-based for identification of glaucoma in retinal images

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.361073Z

Source-reported events for the cited work

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Observation 68cec960-43c8-448c-8a58-edb8ddaf6f4a · outbound

This paper cites Transformers in medical imaging: A survey.Medical Image Analysis, 88:102802, 2023.

Mask of truth: model sensitivity to unexpected regions of medical images Transformers in medical imaging: A survey.Medical Image Analysis, 88:102802, 2023

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.741720Z

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Observation 5f77afac-7865-420f-9e39-f8a31920e18c · outbound

This paper cites Lt-vit: A vision transformer for multi-label chest x-ray classification.

Mask of truth: model sensitivity to unexpected regions of medical images Lt-vit: A vision transformer for multi-label chest x-ray classification

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.348640Z

Source-reported events for the cited work

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Observation fa7a34cb-ec53-4090-8108-9a60dde14b39 · outbound

This paper cites Detecting glaucoma from fundus photographs using deep learning without convolutions: transformer for improved generalization.Ophthal- mology science, 3(1):100233, 2023.

Mask of truth: model sensitivity to unexpected regions of medical images Detecting glaucoma from fundus photographs using deep learning without convolutions: transformer for improved generalization.Ophthal- mology science, 3(1):100233, 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.340809Z

Source-reported events for the cited work

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Observation a5a4e858-4071-4810-a460-fe3b2f8734bd · outbound

This paper cites Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning.

Mask of truth: model sensitivity to unexpected regions of medical images Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.750351Z

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Observation 6f08b4e2-3b87-4cb0-b37a-c24bd6ca346e · outbound

This paper cites Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data.

Mask of truth: model sensitivity to unexpected regions of medical images Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.753949Z

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Observation 3a594dd4-f6da-4ecf-8edf-36d396fceabb · outbound

This paper cites Visual–language foundation models in medicine.The Visual Computer, pages 1–20, 2024.

Mask of truth: model sensitivity to unexpected regions of medical images Visual–language foundation models in medicine.The Visual Computer, pages 1–20, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.333593Z

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Observation 1ab86a22-7071-41dc-9382-a51a20db2517 · outbound

This paper cites VisionUnite: A Vision-Language Foundation Model for Ophthalmology Enhanced with Clinical Knowledge.

Mask of truth: model sensitivity to unexpected regions of medical images VisionUnite: A Vision-Language Foundation Model for Ophthalmology Enhanced with Clinical Knowledge

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.760258Z

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Observation 7a37a12c-cc83-4db7-a04c-c9298a94cd27 · outbound

This paper cites Shortcutlearningindeepneural networks.

Mask of truth: model sensitivity to unexpected regions of medical images Shortcutlearningindeepneural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.327060Z

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Observation e42eefc0-e563-41fc-bf20-9b387b68f112 · outbound

This paper cites shortcuts.

Mask of truth: model sensitivity to unexpected regions of medical images shortcuts

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.320662Z

Source-reported events for the cited work

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Observation f9f4264a-e481-4cfb-9314-119937a1f837 · outbound

This paper cites Detecting and mitigating the clever hans effect in medical imaging: A scoping review.Journal of Imaging Informatics in Medicine, pages 1–17, 2024.

Mask of truth: model sensitivity to unexpected regions of medical images Detecting and mitigating the clever hans effect in medical imaging: A scoping review.Journal of Imaging Informatics in Medicine, pages 1–17, 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.313484Z

Source-reported events for the cited work

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Observation afb82f1c-f554-44a2-8a40-20d3ed01bec6 · outbound

This paper cites An unex- pected confounder: how brain shape can be used to classify mri scans? InMedical Imaging with Deep Learning, 2024.

Mask of truth: model sensitivity to unexpected regions of medical images An unex- pected confounder: how brain shape can be used to classify mri scans? InMedical Imaging with Deep Learning, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.305091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a9580497-95a7-44fd-9032-562c6f544a15 · outbound

This paper cites There are no shortcuts to anywhere worth going: Identifying shortcuts in deep learningmodelsformedicalimageanalysis.

Mask of truth: model sensitivity to unexpected regions of medical images There are no shortcuts to anywhere worth going: Identifying shortcuts in deep learningmodelsformedicalimageanalysis

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.298398Z

Source-reported events for the cited work

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Observation 4621bbda-645a-47a1-b710-2a1cd5104d1c · outbound

This paper cites Fast diffusion-based counterfactuals for shortcut removal and generation.

Mask of truth: model sensitivity to unexpected regions of medical images Fast diffusion-based counterfactuals for shortcut removal and generation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.291748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e6c59ad3-274d-4784-a634-14c3800db018 · outbound

This paper cites Radedit: stress-testing biomedical vision models via diffusion image editing.

Mask of truth: model sensitivity to unexpected regions of medical images Radedit: stress-testing biomedical vision models via diffusion image editing

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.285315Z

Source-reported events for the cited work

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Observation 6209ce36-ba57-4a63-9ffe-3208d122f7d7 · outbound

This paper cites (de)constructing bias on skin lesion datasets.

Mask of truth: model sensitivity to unexpected regions of medical images (de)constructing bias on skin lesion datasets

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.279586Z

Source-reported events for the cited work

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Observation f7a170ff-c0ce-4a79-8457-011e3f7f68f5 · outbound

This paper cites Deep learning on fundus images detects glau- coma beyond the optic disc.Scientific Reports, 11(1):20313, 2021.

Mask of truth: model sensitivity to unexpected regions of medical images Deep learning on fundus images detects glau- coma beyond the optic disc.Scientific Reports, 11(1):20313, 2021

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.272294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e45d6fc2-6a46-468b-9442-2b2277fc1f19 · outbound

This paper cites Generalisation chal- lenges in deep learning models for medical imagery: insights from external valida- tionofcovid-19classifiers.

Mask of truth: model sensitivity to unexpected regions of medical images Generalisation chal- lenges in deep learning models for medical imagery: insights from external valida- tionofcovid-19classifiers

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.265353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7a8d1793-71cb-4235-8e68-af1bb3962112 · outbound

This paper cites Optimising chest x-rays for image analysis by identi- fying and removing confounding factors.

Mask of truth: model sensitivity to unexpected regions of medical images Optimising chest x-rays for image analysis by identi- fying and removing confounding factors

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.256611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c2050af6-735b-4b2a-8c99-149540fb7594 · outbound

This paper cites Shortcut learning in medical image segmentation.

Mask of truth: model sensitivity to unexpected regions of medical images Shortcut learning in medical image segmentation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.247203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8c42f6d2-fb20-46d6-9fa8-324de4c7d689 · outbound

This paper cites Source matters: Source dataset impact on model robustness in medical imaging.

Mask of truth: model sensitivity to unexpected regions of medical images Source matters: Source dataset impact on model robustness in medical imaging

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.238888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 01f15ae3-95cd-4be8-ad76-07bbf6d50303 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Mask of truth: model sensitivity to unexpected regions of medical images Imagenet: A large-scale hierarchical image database

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.231859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 097b6b2f-6191-430d-84a8-7ac9a51755b5 · outbound

This paper cites Radimagenet: an open radiologic deep learning research dataset for effective trans- fer learning.

Mask of truth: model sensitivity to unexpected regions of medical images Radimagenet: an open radiologic deep learning research dataset for effective trans- fer learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.223990Z

Source-reported events for the cited work

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Observation 8877b258-6ff0-4599-a633-07a1d05c0dca · outbound

This paper cites an unresolved cited work.

Mask of truth: model sensitivity to unexpected regions of medical images Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:53:46.215078Z

Source-reported events for the cited work

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Observation 2614784f-d1a2-4e95-8f15-3b529f71ed5f · outbound

This paper cites Transparent medical image ai via an image–text foundation model grounded in medical literature.

Mask of truth: model sensitivity to unexpected regions of medical images Transparent medical image ai via an image–text foundation model grounded in medical literature

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.208087Z

Source-reported events for the cited work

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Observation c7383ecc-9224-4943-bc04-60a2cb23d94c · outbound

This paper cites Concept bottleneck models.

Mask of truth: model sensitivity to unexpected regions of medical images Concept bottleneck models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.198209Z

Source-reported events for the cited work

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Observation 60df08c8-f055-4d62-a978-6d29258f7e2a · outbound

This paper cites Padchest: A large chest x-ray image dataset with multi-label annotated reports.

Mask of truth: model sensitivity to unexpected regions of medical images Padchest: A large chest x-ray image dataset with multi-label annotated reports

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.188299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d8bc09a8-51bc-4e98-8f74-9ff8cf2f6fcb · outbound

This paper cites Chexpert: A large chest radiograph dataset with uncertainty labels and ex- pert comparison.

Mask of truth: model sensitivity to unexpected regions of medical images Chexpert: A large chest radiograph dataset with uncertainty labels and ex- pert comparison

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.181013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 88e801ca-9347-4dfa-8d57-8c406cb1a057 · outbound

This paper cites Chestx-ray8: Hospital-scale chest x-ray database and bench- marks on weakly-supervised classification and localization of common thorax dis- eases.

Mask of truth: model sensitivity to unexpected regions of medical images Chestx-ray8: Hospital-scale chest x-ray database and bench- marks on weakly-supervised classification and localization of common thorax dis- eases

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.173449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fbe80a51-2ffd-46d6-9198-cba313ad42cf · outbound

This paper cites Chexmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images.

Mask of truth: model sensitivity to unexpected regions of medical images Chexmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.166515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation afae7da9-f4e8-4156-bf41-bbf7c7da1821 · outbound

This paper cites Reverse classi- fication accuracy: predicting segmentation performance in the absence of ground truth.

Mask of truth: model sensitivity to unexpected regions of medical images Reverse classi- fication accuracy: predicting segmentation performance in the absence of ground truth

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.157870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 35dcfd1b-4c49-4cbe-9de6-33c3d8ede818 · outbound

This paper cites Cháks.u: A glaucoma specific fundus image database.Scientific data, 10(1):70, 2023.

Mask of truth: model sensitivity to unexpected regions of medical images Cháks.u: A glaucoma specific fundus image database.Scientific data, 10(1):70, 2023

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.149333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4aa559c8-7390-44d1-b2a8-3af4c998260d · outbound

This paper cites Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation.

Mask of truth: model sensitivity to unexpected regions of medical images Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.140879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e74a7ce-9d2f-46de-adde-72f66636229b · outbound

This paper cites Densely connected convolutional networks.

Mask of truth: model sensitivity to unexpected regions of medical images Densely connected convolutional networks

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.835029Z

Source-reported events for the cited work

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Observation c984d449-b128-491b-9568-7a92661e55e1 · outbound

This paper cites In the picture: Medical imaging datasets, artifacts, and their living review.arXiv preprint arXiv:2501.10727, 2025.

Mask of truth: model sensitivity to unexpected regions of medical images In the picture: Medical imaging datasets, artifacts, and their living review.arXiv preprint arXiv:2501.10727, 2025

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Resolution: verified exact; raw_fallback, observed 2026-08-11T21:53:45.978163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dc9e8708-1b8b-4cff-b902-f7345c8f079f · outbound

This paper cites Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

Mask of truth: model sensitivity to unexpected regions of medical images Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.840310Z

Source-reported events for the cited work

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Observation b35321b0-55a4-4973-bed5-eff2d206db8d · outbound

This paper cites Fast implementation of delong’s algorithm for comparing the areas under correlated receiver operating characteristic curves.IEEE Signal Processing Letters, 21(11):1389–1393, 2014.

Mask of truth: model sensitivity to unexpected regions of medical images Fast implementation of delong’s algorithm for comparing the areas under correlated receiver operating characteristic curves.IEEE Signal Processing Letters, 21(11):1389–1393, 2014

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.124337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 85370209-1007-48d9-a11a-988f3656dd34 · outbound

This paper cites Classification of copd with multiple in- stance learning.

Mask of truth: model sensitivity to unexpected regions of medical images Classification of copd with multiple in- stance learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.114823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 182ea064-74d1-4154-8b61-9ac6f476dd90 · outbound

This paper cites A new method using deep learning to predict the response to cardiac resyn- chronization therapy.

Mask of truth: model sensitivity to unexpected regions of medical images A new method using deep learning to predict the response to cardiac resyn- chronization therapy

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.107531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dac4bb9c-657b-4cbf-ab32-6f74c787aedf · outbound

This paper cites Visualizing data using t-sne.Jour- nal of machine learning research, 9(11), 2008.

Mask of truth: model sensitivity to unexpected regions of medical images Visualizing data using t-sne.Jour- nal of machine learning research, 9(11), 2008

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.851617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aa98d03-85ff-4b24-aa46-c96ac712a35f · outbound

This paper cites A unified approach to interpreting model pre- dictions.

Mask of truth: model sensitivity to unexpected regions of medical images A unified approach to interpreting model pre- dictions

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.094930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e9e78d42-64e2-4bf5-902b-91fd17656d5b · outbound

This paper cites Navigating the maze of explainable ai: A systematic approach to evaluating methods and metrics.

Mask of truth: model sensitivity to unexpected regions of medical images Navigating the maze of explainable ai: A systematic approach to evaluating methods and metrics

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.087578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4d4e511d-70e3-42dd-9586-fe87447a015e · outbound

This paper cites Impossibility theorems for feature attribution.Proceedings of the National Academy of Sciences, 121(2):e2304406120, 2024.

Mask of truth: model sensitivity to unexpected regions of medical images Impossibility theorems for feature attribution.Proceedings of the National Academy of Sciences, 121(2):e2304406120, 2024

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.079330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f7df0a0e-547d-4a8b-92f9-3e0a8b9c2c11 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Mask of truth: model sensitivity to unexpected regions of medical images Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T21:53:45.865829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf1f39a6-f3cd-4d07-913b-e13c7be16b31 · outbound

This paper cites Automatic detection of glaucoma via fundus imaging and artificial intelligence: A review.Survey of ophthalmology, 68(1):17–41, 2023.

Mask of truth: model sensitivity to unexpected regions of medical images Automatic detection of glaucoma via fundus imaging and artificial intelligence: A review.Survey of ophthalmology, 68(1):17–41, 2023

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.066849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9c433e25-b497-4c2e-97a0-5a8e3446f50f · outbound

This paper cites Optic disc diameter influences the ability to detect glaucomatous disc damage.Acta ophthalmologica, 71(1):122–129, 1993.

Mask of truth: model sensitivity to unexpected regions of medical images Optic disc diameter influences the ability to detect glaucomatous disc damage.Acta ophthalmologica, 71(1):122–129, 1993

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.058867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ab3d3cb3-1b5c-460f-b422-bfb4c9572ace · outbound

This paper cites Optic disc size, an important consideration in the glaucoma evaluation.

Mask of truth: model sensitivity to unexpected regions of medical images Optic disc size, an important consideration in the glaucoma evaluation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.052005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 505e9d2a-0ef3-4021-a17e-7a0eb41a30ba · outbound

This paper cites Model-based cleaning of the quilt-1m pathology dataset for text-conditional image synthesis.

Mask of truth: model sensitivity to unexpected regions of medical images Model-based cleaning of the quilt-1m pathology dataset for text-conditional image synthesis

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.045493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d7e8ab45-8cbb-48c9-a462-52e157e1fe82 · outbound

This paper cites Investigating the quality of dermamnist and fitzpatrick17k dermatological image datasets.Scientific Data, 12(1):196, 2025.

Mask of truth: model sensitivity to unexpected regions of medical images Investigating the quality of dermamnist and fitzpatrick17k dermatological image datasets.Scientific Data, 12(1):196, 2025

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.038026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f85c0307-7ee6-4a30-9f31-c3f950e649cc · outbound

This paper cites Navigating the landscape of multimodal AI in medicine: a scoping review on technical challenges and clinical applications.

Mask of truth: model sensitivity to unexpected regions of medical images Navigating the landscape of multimodal AI in medicine: a scoping review on technical challenges and clinical applications

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:53:45.914827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d71fd064-d754-46f2-84b4-9410dd8d0cdd · outbound

This paper cites The risk of shortcut- ting in deep learning algorithms for medical imaging research.Scientific Reports, 14(1):29224, 2024.

Mask of truth: model sensitivity to unexpected regions of medical images The risk of shortcut- ting in deep learning algorithms for medical imaging research.Scientific Reports, 14(1):29224, 2024

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.030487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 12183bb8-2bbe-4103-8555-edbe2025b17e · outbound

This paper cites Are vision transformers robust to spurious correlations? International Journal of Computer Vision, 132(3):689–709, 2024.

Mask of truth: model sensitivity to unexpected regions of medical images Are vision transformers robust to spurious correlations? International Journal of Computer Vision, 132(3):689–709, 2024

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.022060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6b7ffe8d-1536-4f4f-ad28-b574dd890f3e · outbound

This paper cites Metrics reloaded: recommendations for image analysis validation.

Mask of truth: model sensitivity to unexpected regions of medical images Metrics reloaded: recommendations for image analysis validation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:53:46.013119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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