Pith. sign in

Paper Citation Record · LEDGER

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging

As of 21 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2508.18613.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.18613 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:00:32.678260Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy37
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 232f8062-5d3f-4692-87e0-04a5982edaf6 · outbound

This paper cites A survey on self-supervised methods for visual representation learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging A survey on self-supervised methods for visual representation learning

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.387051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.475912Z digest=sha256:32e550bafa624f26134270cfa3c27de2696f0388b3211c90f7d7c46862de05f7

Observation 0143d054-d14d-4bb9-8968-3da9ef8245f1 · outbound

This paper cites Self-supervised learning for medical image analysis: a comprehensive review.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Self-supervised learning for medical image analysis: a comprehensive review

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.371582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.482104Z digest=sha256:194e333ec19a26a6708ac8569a6e0d10636f60b40a79705ecf01477903c1e70e

Observation 27337f1c-4807-4a01-be48-f319876758c3 · outbound

This paper cites Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.356422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.486829Z digest=sha256:40efdfb5a0554659e4fba43623ae9b704fb8afccea47c9ff772b94d454fd4dc7

Observation 0e1c4a6f-69ec-4efa-815d-0b6341a38849 · outbound

This paper cites Distributed contrastive learning for medical image segmentation.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Distributed contrastive learning for medical image segmentation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.341479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.491634Z digest=sha256:514fb9d7174f3e837ef6551b371efcf9a8ca7a7658ff5073e8d67e73058d1145

Observation 31d21a7d-393d-4ebb-a226-9189c7a46a76 · outbound

This paper cites Mim: Mask in mask self-supervised pre-training for 3d medical image analysis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Mim: Mask in mask self-supervised pre-training for 3d medical image analysis

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.326525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.497906Z digest=sha256:a212ab743bc482e112cd1a90e6aa6c23df97a03b41283580392cfcd471ffb0d8

Observation 0628cae4-e343-4352-9d39-6b1b5e6eda01 · outbound

This paper cites Robson, Brett Marinelli, Mingqian Huang, Amish Doshi, Adam Jacobi, Chendi Cao, Katherine E.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Robson, Brett Marinelli, Mingqian Huang, Amish Doshi, Adam Jacobi, Chendi Cao, Katherine E

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T17:00:32.502834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:00:32.502834Z digest=sha256:3cbbbe5b02a86da515e27fc8743d7ac7aefc24fa6b1fef61776a4927e5ac1462

Observation 68002d71-5ff9-47a3-9b4e-a0a8439117f6 · outbound

This paper cites Vis-mae: An efficient self-supervised learning approach on medical image segmentation and classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Vis-mae: An efficient self-supervised learning approach on medical image segmentation and classification

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.300788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.507805Z digest=sha256:a3a42f58990dc2b765320f7e865af5c8719fca23ac1dc72351ebed3213366a6b

Observation d5193d1f-85c6-4c53-85a9-8ec52f000ed2 · outbound

This paper cites Rotation- oriented collaborative self-supervised learning for retinal disease diagnosis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Rotation- oriented collaborative self-supervised learning for retinal disease diagnosis

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.284966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.512890Z digest=sha256:2dd47d13f2f7197d8847050a1ad27a29a0ef0de83e4078fb6e8dc0ab6e113415

Observation d09c7e6a-b2ab-49de-af2a-1dc733c6c21c · outbound

This paper cites A simple framework for contrastive learning of visual representations.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging A simple framework for contrastive learning of visual representations

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T17:00:32.518503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:00:32.518503Z digest=sha256:8cca9d23b9583136b6479d15e7e21cbc7b65e4fba16c365fb789984280ca58b9

Observation b2690b9f-a20e-44d4-ad7f-9aca67977b05 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Momentum contrast for unsupervised visual representation learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T17:00:32.522996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:00:32.522996Z digest=sha256:91ae8ffde03ee90408440d2dc52ea48763bcfbb14fae7e9ceae9e6bbb06224b7

Observation 167301a2-9e94-46f8-a7e2-e2802bf33dd0 · outbound

This paper cites UKSSL: Underlying knowledge based semi- supervised learning for medical image classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging UKSSL: Underlying knowledge based semi- supervised learning for medical image classification

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.247123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.528202Z digest=sha256:250516f190d5cc981c170202596883dd8eefefc68964de9b5a7665362b66fce9

Observation 0fce12b6-81fe-4846-91e5-c646cd88ca79 · outbound

This paper cites Moco pretraining improves representation and transferability of chest x-ray models.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Moco pretraining improves representation and transferability of chest x-ray models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.231079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.532555Z digest=sha256:af22bef5f2121b875b3d01387cc067393ee1bad66fc72809fc52c556d2e53789

Observation e494bbe0-dd63-4235-bcf6-b85d7692c8eb · outbound

This paper cites Gloria: A multimodal global-local rep- resentation learning framework for label-efficient medical image recognition.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Gloria: A multimodal global-local rep- resentation learning framework for label-efficient medical image recognition

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.213129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.537503Z digest=sha256:baef464367baf12142e094a22ce3cdceddd214b542575c4e71fd0ec05066a86a

Observation 5490bc22-fe64-40a7-a3f4-803605cb5dd5 · outbound

This paper cites Making the most of text semantics to improve biomedical vision–language processing.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Making the most of text semantics to improve biomedical vision–language processing

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.197458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.541822Z digest=sha256:d67bcdcdd2d32672ac3308ffba23cc7251921dc432ebbbf9c5d54e2e6ff64c95

Observation b3d83d30-307d-4be5-a2a8-01cdf57c35a7 · outbound

This paper cites Self pre-training with masked autoencoders for medical image classification and segmentation.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Self pre-training with masked autoencoders for medical image classification and segmentation

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.182161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.546603Z digest=sha256:137f62821406a549f029be9d94880c413cf7aaf66ae9dc3267a5d3344946bee3

Observation 1b053df4-9a6a-49a6-9f95-08f849a91db5 · outbound

This paper cites Advancing V olumetric Medical Image Segmentation via Global-Local Masked Autoencoders.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Advancing V olumetric Medical Image Segmentation via Global-Local Masked Autoencoders

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.166506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.551521Z digest=sha256:40aac3aee403ff738301b73ee0e25cedd88fc6b00645e080461dede39572b60b

Observation b16e863f-ca90-4557-aa57-814e8fcfae45 · outbound

This paper cites Swin MAE: masked autoencoders for small datasets.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Swin MAE: masked autoencoders for small datasets

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.151624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.555736Z digest=sha256:044c3add9b33b59b651f5bfa659eff237616b9d4e1c9010cd7fd860ac2862ad3

Observation 9bf8c2bb-0546-4b57-9211-5db32105156e · outbound

This paper cites Unest: local spatial representation learning with hierarchical transformer for efficient medical segmentation.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Unest: local spatial representation learning with hierarchical transformer for efficient medical segmentation

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.135739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.560048Z digest=sha256:baab0cd948dde4aec60a15f39eeef5317329a31378f210f47971f8d34d0c5ed9

Observation b7e7b30c-6734-4678-9e80-0c6786dfbf01 · outbound

This paper cites Video-CT MAE: Self-supervised Video-CT Domain Adaptation for Vertebral Fracture Diagnosis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Video-CT MAE: Self-supervised Video-CT Domain Adaptation for Vertebral Fracture Diagnosis

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.120818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.564240Z digest=sha256:a04717b1e1ff69ff3b934f6edfd9200d7a33682cf2dd68e1eb74136e746a4ded

Observation 78195710-8df9-454a-a2a9-157445065d1d · outbound

This paper cites Self-supervised pre-training of swin transformers for 3d medical image analysis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Self-supervised pre-training of swin transformers for 3d medical image analysis

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.104685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.569571Z digest=sha256:7feb081fcbd949ac13bcc9087e663892695fd82029227d26916b965024ea0030

Observation c4340c5d-075c-49e0-9771-d2d46f9e85d7 · outbound

This paper cites Mining multi-label data.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Mining multi-label data

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.089490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.574031Z digest=sha256:6d16666093b0403b6b6285cd465f1b3e36687800006d563d520c254e3ee43d83

Observation dabff964-08d2-43ef-948d-7791eb88c86f · outbound

This paper cites Learning multi-label scene classifica- tion.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Learning multi-label scene classifica- tion

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.072832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.578335Z digest=sha256:0ad0a3f533eb5ebfdbb3015fa0c83753e25e99755fd89eff806caefe9b711f14

Observation 85bb12ea-debe-424c-abe2-67be29320547 · outbound

This paper cites ML-KNN: A lazy learning approach to multi-label learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging ML-KNN: A lazy learning approach to multi-label learning

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.053836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.582571Z digest=sha256:679453db02be85a19e0c39ba1200d69a222e597614738c3080935bf152177196

Observation d6ce1e5b-6416-4a69-bb0a-c8be304848ac · outbound

This paper cites A kernel method for multi-labelled classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging A kernel method for multi-labelled classification

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.034568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.588269Z digest=sha256:a844aa0b230e15c31d85d51c5fbfec48aac51bee6063f7cd6ef4bc7585ba522a

Observation e18fe432-acc2-4fbe-82db-74be74741d40 · outbound

This paper cites Cnn-rnn: A unified framework for multi-label image classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Cnn-rnn: A unified framework for multi-label image classification

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.018030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.592797Z digest=sha256:6a2c5252dbae27a5e2209d0d47842f2542d426dae05000f922f385341d169ecc

Observation 0624a22e-0e4d-43ad-9d05-d091c91c0716 · outbound

This paper cites Learning spatial regularization with image-level supervisions for multi-label image classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Learning spatial regularization with image-level supervisions for multi-label image classification

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:33.000992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.596965Z digest=sha256:fb676d92c2f8ad2d86abba5921c0644ad67ad05ee7c2728d7764c99f83c4128b

Observation 0a360a4d-34c8-4181-b926-6153d84a1fb4 · outbound

This paper cites Multi-label image recognition with graph con- volutional networks.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Multi-label image recognition with graph con- volutional networks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.984814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.601650Z digest=sha256:4afe426abe3fa912854d27b1249002e976bbab7313ac078065839263cc9f18f8

Observation 9d0fc067-bac4-4fa3-9d75-995c0469096f · outbound

This paper cites Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.968046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.606363Z digest=sha256:0c2cb64743a96719ab2b4548c7c0c3df6b1eca561d91b5e703dd8f3bd184ae85

Observation aa7c04f9-4fea-4564-8966-bd6d8116ab66 · outbound

This paper cites Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.951228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.611200Z digest=sha256:0908d32dcc1dbd6e53d4e0bcdd8b448947d0ea470c6832fe8fd2aad4cd38cc29

Observation 7170eca3-9d22-4af0-b379-b397999aaa1d · outbound

This paper cites Hex: Hierarchical emergence exploitation in self-supervised algorithms.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Hex: Hierarchical emergence exploitation in self-supervised algorithms

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.935524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.615688Z digest=sha256:08cdd484c25f781d6530329fc963e39a024b20a5c1673f809fab4d32dcc8e09f

Observation de7d58cd-fec4-478c-b4e4-d363913b0a23 · outbound

This paper cites Hierarchical multi-granular multi-label contrastive learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Hierarchical multi-granular multi-label contrastive learning

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.918871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.620697Z digest=sha256:fdeb11f28f69e60b2ae0afec25399f71782a1abcc08423d12b233ff17ef59e85

Observation 87812a1c-3b0c-45a9-bfeb-c7eaafd060e6 · outbound

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

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.902485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.625186Z digest=sha256:9be1a9b5324a80de2ba51a057ec656fa94689167fd6666ccb764ab40e53dbff9

Observation 985746b7-6237-4754-a01d-6b05b2892cc1 · outbound

This paper cites Mimic-cxr database.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Mimic-cxr database

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.887470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.629535Z digest=sha256:cafe13798878a5d8db9c1bbf6c1df8d5c23ad3088fd9b152a24505a120266741

Observation d3cd1908-9293-4d61-ac39-6a6856d22284 · outbound

This paper cites Imagegcn: Multi-relational image graph convolutional networks for disease identification with chest x-rays.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Imagegcn: Multi-relational image graph convolutional networks for disease identification with chest x-rays

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.871811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.633592Z digest=sha256:0de9c8c1ba9bf4a6289b29886277176ae645db3d6419d9a22079543c9d3de800

Observation 3b60a1c0-8db2-438e-804e-0619cebf7157 · outbound

This paper cites Scalp- supervised contrastive learning for cardiopulmonary disease classification and localization in chest x-rays using patient metadata.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Scalp- supervised contrastive learning for cardiopulmonary disease classification and localization in chest x-rays using patient metadata

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.853626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.638662Z digest=sha256:fb0a92676fe20a49037beb9f14c4ffc1e1a3edbfc951396a2086b9d0f5c4ee98

Observation 21552bef-0944-41fd-95a1-54e570529505 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Representation Learning with Contrastive Predictive Coding

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T17:00:32.642744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:00:32.642744Z digest=sha256:1387ab941e6e28b8b7288929b1a3c429c2d05a81d23ec9447f5e0d092d4ec112

Observation 8da199d0-fb62-427e-a158-379c322f30aa · outbound

This paper cites Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.837756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.648152Z digest=sha256:052e7041ea3c943218623eec496f6b98006581ab2d9bed4596ecd052bc332f62

Observation f7b45b59-6ad8-465d-a7b0-d08361feccfb · outbound

This paper cites Contrastive learning for multi-label classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Contrastive learning for multi-label classification

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.821251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.652772Z digest=sha256:64d87c74ae60c0650dd9c53cdf1c42ef8aa215a579cee5fedce36532bc2db886

Observation 2c3bb85b-6f98-44b6-b188-099979c0a3b5 · outbound

This paper cites An open access thyroid ultrasound image database.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging An open access thyroid ultrasound image database

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.805584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.658235Z digest=sha256:ba745b2d970264487ab5fedcf6a8861cfd627d3550c82199e048bcedf8f619a3

Observation 87c1e6c7-dc01-4419-a736-9b8dda7d7c1e · outbound

This paper cites Dataset of breast ultrasound images.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Dataset of breast ultrasound images

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.789823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.662920Z digest=sha256:23ec070318d5fb4daae01ab09aba698249389b24a979e8be12971a74961c829b

Observation 28b07eee-c9a9-453a-b5e9-8b3559dda098 · outbound

This paper cites Deep-learning-assisted diagnosis for knee mag- netic resonance imaging: development and retrospective validation of MRNet.PLoS medicine, 15(11):e1002699,.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Deep-learning-assisted diagnosis for knee mag- netic resonance imaging: development and retrospective validation of MRNet.PLoS medicine, 15(11):e1002699,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:00:32.774242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.667846Z digest=sha256:4dd642de22373f89364f867521b2d9be74f2de9f19527edab416cab1a2602062

Observation 3c4d7596-4bda-4753-8458-fab3d6b80353 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T17:00:32.678260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:00:32.678260Z digest=sha256:42b32dec7a86ea28c8e1559ff2a7518b63670737433bf661407635f1fdcb9be5

Observation 3daa768a-5d66-4a28-9adb-79676a753d13 · outbound

This paper cites an unresolved cited work.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Unresolved cited work

Reference 2018

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:00:32.756808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T17:00:32.672589Z digest=sha256:f935f48535a8fc3b9b35efe4061ae15791ebb535e8b0a406c9eb8e087912c77b

Pith citing papers

No inbound Pith citation observations are available.