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Paper Citation Record · LEDGER

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique

As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2507.15915.

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

pith.paper-citation-record.v1
2507.15915 v1

Coverage vector

measured 48 of 48 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

48 of 48 outbound references displayed

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External citation measurements

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Outbound references

Observation 2626edea-9cff-4413-832c-5829c808f729 · outbound

This paper cites Epidemiologi- cal situation of mon- keypox transmission by possible sexual contact: a systematic review.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Epidemiologi- cal situation of mon- keypox transmission by possible sexual contact: a systematic review

Reference 1

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Observation 711a72a3-d2c1-4fa5-9b6e-038f9877b33d · outbound

This paper cites Burden of salmonellosis, campylobacteriosis and liste- riosis: a time series analysis, belgium, 2012 to 2020.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Burden of salmonellosis, campylobacteriosis and liste- riosis: a time series analysis, belgium, 2012 to 2020

Reference 2

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Observation 5d58966e-ba7d-4b5d-88ac-aa8208cca599 · outbound

This paper cites Genomic variability of monkeypox virus among hu- mans, democratic republic of the congo.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Genomic variability of monkeypox virus among hu- mans, democratic republic of the congo

Reference 3

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Observation fe50c69f-a691-40d5-a4f8-727d8dbafdc0 · outbound

This paper cites Mon- keypox: a comprehensive review of transmission, pathogenesis, and man- ifestation.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Mon- keypox: a comprehensive review of transmission, pathogenesis, and man- ifestation

Reference 4

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Observation 6385233c-859a-46f3-a11a-5b749a21a69d · outbound

This paper cites Monkeypox virus emerges from the shadow of its more infamous cousin: fam- ily biology matters.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkeypox virus emerges from the shadow of its more infamous cousin: fam- ily biology matters

Reference 5

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Observation d7948c79-ea36-4239-bfb7-6fdf68acae3c · outbound

This paper cites Re-emerging human monkeypox: a major public-health debacle.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Re-emerging human monkeypox: a major public-health debacle

Reference 6

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Observation b9f0a62d-561f-4572-b52a-878eba2a16d9 · outbound

This paper cites Human monkeypox disease (mpx).

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Human monkeypox disease (mpx)

Reference 7

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Observation 72b329e1-09a0-47ce-bf9c-e676f157ce22 · outbound

This paper cites A global up- date of mpox (monkeypox) in children.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique A global up- date of mpox (monkeypox) in children

Reference 8

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Observation 1ff62c9a-3371-47e0-b067-1af5f1f8705b · outbound

This paper cites Outbreak of human monkeypox in nigeria in 2017–18: a clinical and epidemiological report.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Outbreak of human monkeypox in nigeria in 2017–18: a clinical and epidemiological report

Reference 9

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Observation c13f8caf-6188-4644-8e27-1c86cfabe5a3 · outbound

This paper cites Recent outbreak of monkeypox: implications for pub- lic health recommendations and crisis management in india.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Recent outbreak of monkeypox: implications for pub- lic health recommendations and crisis management in india

Reference 10

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Observation 883c640f-5f38-433f-9578-7d83227ea31f · outbound

This paper cites Monkey- pox virus infection in humans across 16 coun- tries—april–june 2022.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkey- pox virus infection in humans across 16 coun- tries—april–june 2022

Reference 11

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Source-reported events for the cited work

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Observation dd4e4fb9-ffc7-4eb9-a675-44882889023f · outbound

This paper cites Monkeypox virus: a re- emergent threat to humans.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkeypox virus: a re- emergent threat to humans

Reference 12

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Source-reported events for the cited work

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Observation 605dc254-2d2f-453d-8e74-b31def3e463e · outbound

This paper cites Use of artificial intelligence in infectious diseases, in: Artificial intelligence in precision health.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Use of artificial intelligence in infectious diseases, in: Artificial intelligence in precision health

Reference 13

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Observation 2982b66e-6b59-4219-8608-b24102569ac1 · outbound

This paper cites Machine-learning-based disease diagnosis: A comprehensive review , in: Healthcare, MDPI.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Machine-learning-based disease diagnosis: A comprehensive review , in: Healthcare, MDPI

Reference 14

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Observation 04046942-31c9-4b46-859f-1ba598578954 · outbound

This paper cites Ex- plainable artificial intelligence (xai) in deep learning-based medical image analysis.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Ex- plainable artificial intelligence (xai) in deep learning-based medical image analysis

Reference 15

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Observation d198438f-af92-4875-ba95-289030288235 · outbound

This paper cites A cnn-based methodology for breast can- cer diagnosis using thermal images.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique A cnn-based methodology for breast can- cer diagnosis using thermal images

Reference 16

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Observation a5e3f5a0-5e9e-48a7-a52a-ac64d8331f12 · outbound

This paper cites Medical image analysis using deep learning algorithms.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Medical image analysis using deep learning algorithms

Reference 17

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Observation 3a8aa58e-1f39-40cd-a40a-181f57da0b48 · outbound

This paper cites Transfer learning for medical im- age classification: a litera- ture review.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Transfer learning for medical im- age classification: a litera- ture review

Reference 18

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Observation 2a7c515c-baa6-46cc-bfd3-c5bb854fe752 · outbound

This paper cites Transformers in medical image analysis.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Transformers in medical image analysis

Reference 19

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Source-reported events for the cited work

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Observation ab546a48-b7b5-4f9a-aa42-e40a5ed57932 · outbound

This paper cites Poxnet22: A fine-tuned model for the classification of monkeypox disease using transfer learning.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Poxnet22: A fine-tuned model for the classification of monkeypox disease using transfer learning

Reference 21

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Observation 1ccbd538-ad6d-417c-ac3f-fcae4c3ca7dc · outbound

This paper cites Monkey- pox diagnosis with inter- pretable deep learning.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkey- pox diagnosis with inter- pretable deep learning

Reference 22

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Observation 290ed20c-755f-4f44-92d0-f135ba656392 · outbound

This paper cites Attention to monkeypox: An 41 inter- pretable monkeypox detection technique using attention mecha- nism.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Attention to monkeypox: An 41 inter- pretable monkeypox detection technique using attention mecha- nism

Reference 23

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Observation 6f7cb07d-abac-40dc-8b3e-c28366399f4f · outbound

This paper cites Monkeypox virus detection using pre- trained deep learning-based approaches.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkeypox virus detection using pre- trained deep learning-based approaches

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation dd689bff-edcb-4bfb-9919-e49447be5682 · outbound

This paper cites Monkeypox de- tection using deep neural networks.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkeypox de- tection using deep neural networks

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e0abb883-3911-44be-b2a4-a26da52e5346 · outbound

This paper cites Hyper-parameter tuned deep learning approach for ef- fective human monkeypox disease detection.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Hyper-parameter tuned deep learning approach for ef- fective human monkeypox disease detection

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2e7ebefe-4487-424f-b0ab-9210da82ddeb · outbound

This paper cites Attention learning models using local zernike moments-based normalized images and convolutional neural networks for skin lesion classification.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Attention learning models using local zernike moments-based normalized images and convolutional neural networks for skin lesion classification

Reference 28

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Observation fd0127be-ec7f-4d6d-b155-d5950059068a · outbound

This paper cites Mox-net: Multi-stage deep hybrid feature fusion and selection frame- work for mon- keypox classification.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Mox-net: Multi-stage deep hybrid feature fusion and selection frame- work for mon- keypox classification

Reference 29

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Observation 6d0ed683-39c6-4001-8693-b44e2d52b369 · outbound

This paper cites S., Hossain, M.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique S., Hossain, M

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cb4aaeef-7388-4700-9cf6-bb624d9d668b · outbound

This paper cites Meta- heuristics optimization-based ensemble of deep neural net- works for mpox disease de- tection.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Meta- heuristics optimization-based ensemble of deep neural net- works for mpox disease de- tection

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 339d35f0-43f6-4ffd-a16f-9c1f78098450 · outbound

This paper cites Y.,& Sahin, V.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Y.,& Sahin, V

Reference 32

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0eaa87a9-fea1-41a0-a651-f0424d44b686 · outbound

This paper cites B.G., Rombach, H.D., 1994.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique B.G., Rombach, H.D., 1994

Reference 33

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Source-reported events for the cited work

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Observation b3c54076-913e-43c2-9ec3-1ff9e87f5907 · outbound

This paper cites The effectiveness of data augmenta- tion in image classification using deep learning.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique The effectiveness of data augmenta- tion in image classification using deep learning

Reference 34

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Source-reported events for the cited work

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Observation f86e4e05-4c6a-49ce-88ec-94d671d1fb51 · outbound

This paper cites Improving deep learning with generic data aug- mentation , in: 2018 IEEE sympo- sium series on computational intelligence (SSCI), IEEE.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Improving deep learning with generic data aug- mentation , in: 2018 IEEE sympo- sium series on computational intelligence (SSCI), IEEE

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 38cfe801-992c-43c5-a4e8-0d3bdd0a4f43 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 458c737b-64ef-4597-a787-58c8931ba68a · outbound

This paper cites 4510– 4520.https://doi.org/10.1109/CVPR.2018.00474.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique 4510– 4520.https://doi.org/10.1109/CVPR.2018.00474

Reference 38

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5769744f-3fad-44a2-9d84-195749eab72e · outbound

This paper cites Re- thinking the inception architecture for computer vision , in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Re- thinking the inception architecture for computer vision , in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 39

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unresolved
no resolver link, observed 2026-08-06T15:27:56.593027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 11334199-acac-4c6e-bd60-7103f57a002a · outbound

This paper cites an unresolved cited work.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Unresolved cited work

Reference 40

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unresolved
raw_fallback, observed 2026-08-06T15:27:57.614005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e72e0542-28f8-4980-9e8c-e69e922995b0 · outbound

This paper cites Optimization methods for large- scale machine learning.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Optimization methods for large- scale machine learning

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-06T15:27:57.606055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 193f07bb-8c23-4019-8cc4-fbc3007a950d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Adam: A Method for Stochastic Optimization

Reference 42

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f42f0673-cd27-4b58-849d-4135e5f4ab02 · outbound

This paper cites R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Ba- tra, D.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Ba- tra, D

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d8d9a32f-3d7f-4617-84e5-dddbdc2cb737 · outbound

This paper cites Multimedia Tools and Applications 83, 71909– 71923.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Multimedia Tools and Applications 83, 71909– 71923

Reference 44

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verified exact
doi, observed 2026-08-06T15:27:56.695545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6770bb08-4f9c-45c8-ab8f-b9abfe308fb9 · outbound

This paper cites The Effectiveness of Data Augmentation in Image Classification using Deep Learning.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique The Effectiveness of Data Augmentation in Image Classification using Deep Learning

Reference 45

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unresolved
no resolver link, observed 2026-08-06T15:27:56.608532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d9043ff1-0de2-475a-b1ba-184875ae4533 · outbound

This paper cites External validity.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique External validity

Reference 46

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malformed identifier
no resolver link, observed 2026-08-06T15:27:56.610707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:27:56.610707Z digest=sha256:3ad2acd62131b2c7dd30d09cc22a3fd5b313c98625a26cd2c6dad6dbc8856c22

Observation 00c9cd36-e31a-4377-93b3-f961bbacb031 · outbound

This paper cites The precision-recall plot is more informative than the roc plot when evaluating bi- nary classifiers on imbalanced datasets.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique The precision-recall plot is more informative than the roc plot when evaluating bi- nary classifiers on imbalanced datasets

Reference 47

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unresolved
no resolver link, observed 2026-08-06T15:27:56.612897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 27aa03d8-6718-41c1-ad86-478a67ec6e54 · outbound

This paper cites The class imbalance problem in deep learning.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique The class imbalance problem in deep learning

Reference 48

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malformed identifier
doi_truncated, observed 2026-08-06T15:27:56.641670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 158f9a6e-cdba-4595-a30e-8fe69388ead0 · outbound

This paper cites A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity

Reference 49

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verified exact
local_arxiv, observed 2026-08-06T15:27:56.889508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T15:27:56.616773Z digest=sha256:4c6a8a05a9706e128cec9831d7050831423351b4ecde922568eb3fe16d3351c5

Observation 943ad315-c66f-4ed3-9f1b-f39089c7060e · outbound

This paper cites Monkeypox Skin Lesion Detection Using Deep Learning Models: A Feasibility Study.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Monkeypox Skin Lesion Detection Using Deep Learning Models: A Feasibility Study

Reference 50

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verified exact
local_arxiv, observed 2026-08-06T15:27:56.807518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T15:27:56.618768Z digest=sha256:5725a10534994b931781f06398edb3f480e68e2dcbb5a853d29d80181b7b85ea

Observation dc679168-497a-4cc6-abe2-904b62eafebd · outbound

This paper cites Journal of Sensor and Actuator Networks 9, 54.https://doi.org/10.3390/jsan9040054 43.

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique Journal of Sensor and Actuator Networks 9, 54.https://doi.org/10.3390/jsan9040054 43

Reference 2020

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verified exact
doi, observed 2026-08-06T15:27:56.663637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T15:27:56.597494Z digest=sha256:f58dac3caf0089d6e0a9c0046363474b3ce14d1110c34f80308c5262bb276ccd

Pith citing papers

No inbound Pith citation observations are available.