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Paper Citation Record · LEDGER

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.16916.

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

pith.paper-citation-record.v1
2607.16916 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:37:05.713857Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

37 of 37 outbound references displayed

  • verified exact17
  • verified fuzzy0
  • unresolved18
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1c39360-575c-4d3a-892d-35798585626f · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 1

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 51c836ea-50d5-4102-8828-ce2f13f8da40 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 2

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Observation ab43d291-f7ce-4d46-97be-0730f6b220bd · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 3

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b5e798e4-43c2-4367-ab60-62a564bdd774 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 4

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Observation bf5520f0-7005-4683-a772-7115c71a5959 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-01T19:37:01.865088Z digest=sha256:cdcbedc261ca96be6bd141b542bd6cf6d2cc0b6540a4cb771b3fae79a17d6998

Observation 2ec1b665-a75f-425c-84e7-4a2ac2c29de5 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 6

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation cedc33b4-4a20-4f9d-aee7-9d0212754566 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 7

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Observation 8c46bea4-976e-4b4e-be72-07e074ec408d · outbound

This paper cites Medical Knowledge Integration into Reinforcement Learning Algorithms for Dynamic Treatment Regimes.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Medical Knowledge Integration into Reinforcement Learning Algorithms for Dynamic Treatment Regimes

Reference 8

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 965fe78b-1979-43cc-b067-8f84ef5d3c03 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 9

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Observation d8398f9b-46bb-47c4-9d47-c074b101def9 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 10

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Observation 1057514f-6f07-4ac9-9937-6d5893beffa2 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 2b533266-cf72-419e-96f6-f9d45dbfff55 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 12

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Observation 3e9a4c71-05c7-459f-b6c9-7ae878953a57 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 13

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ad1213a7-4008-4e6d-8265-0f767681b85b · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 14

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 396c1640-c4b3-494c-a3e5-4329c147a494 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 15

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doi, observed 2026-08-01T19:38:25.990022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c662dbae-dc13-4204-85d9-30926baf939d · outbound

This paper cites Oncology Simulation Model: A Comprehensive and Innovative Approach to Estimate and Project Prevalence and Survival in Oncology.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Oncology Simulation Model: A Comprehensive and Innovative Approach to Estimate and Project Prevalence and Survival in Oncology

Reference 16

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 939d29e4-863a-495b-9955-1d2994c799c2 · outbound

This paper cites Prediction of Cancer Treatment Effectiveness and Patient Outcomes using Machine Learning Classification Approaches - A Review.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Prediction of Cancer Treatment Effectiveness and Patient Outcomes using Machine Learning Classification Approaches - A Review

Reference 17

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 58ed4eb2-9861-4742-acc3-c77bae8fd521 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0143d716-8a72-4618-9125-c7e913b3daee · outbound

This paper cites Artificial Intelligence in Oncology: Current Capabilities, Future Opportunities, and Ethical Considerations.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Artificial Intelligence in Oncology: Current Capabilities, Future Opportunities, and Ethical Considerations

Reference 19

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 68a081b6-0f24-4f25-8812-7dad459883e7 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e01ece85-8c8d-4005-943b-0f8727e64138 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 81d0715e-4979-4378-b787-4faac17f028d · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 22

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Unavailable: canonical work link unavailable.

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Observation 10e0a36f-f615-4ca8-a251-32515a43ca32 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 23

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Observation 26052d84-b72a-460d-bea1-a05823595bfd · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 127fac9e-2621-439d-a5e3-f81da2a0ddb3 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4c0071b8-cf76-4840-9e46-853a68c0fdd1 · outbound

This paper cites A review on modeling tumor dynamics and agent reward functions in reinforcement learning based therapy optimization.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework A review on modeling tumor dynamics and agent reward functions in reinforcement learning based therapy optimization

Reference 26

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Source-reported events for the cited work

retraction . Source: retraction watch record 62368, observed 2026-07-08T21:54:04.204263+00:00. This notice travels one citation hop only.

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Observation 264bb154-c428-4537-afdc-2c07701085b0 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 27

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Observation b17de782-c69a-4e31-a662-96708516f9cf · outbound

This paper cites Regression analysis of multivariate incomplete failure time data by modeling marginal distributions.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Regression analysis of multivariate incomplete failure time data by modeling marginal distributions

Reference 28

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Unavailable: canonical work link unavailable.

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Observation a3ab47f2-3cde-4a2d-b85c-fc6843c67f25 · outbound

This paper cites Automating the optimization of proton PBS treatment planning for head and neck cancers using policy gradient‐based deep reinforcement learning.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Automating the optimization of proton PBS treatment planning for head and neck cancers using policy gradient‐based deep reinforcement learning

Reference 29

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no resolver link, observed 2026-08-01T19:37:04.854548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e32da428-bc78-409e-80b5-09004b485423 · outbound

This paper cites Breast radiation therapy fluence painting with multi‐agent deep reinforcement learning.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Breast radiation therapy fluence painting with multi‐agent deep reinforcement learning

Reference 30

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Unavailable: canonical work link unavailable.

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Observation 371bf13d-87b7-40f6-a842-c0321fb30055 · outbound

This paper cites Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning

Reference 31

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Unavailable: canonical work link unavailable.

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Observation 5679ddc7-4dd6-4fcf-adcc-63257e42c0f5 · outbound

This paper cites Human -like intelligent automatic treatment planning of head and neck cancer radiation therapy.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Human -like intelligent automatic treatment planning of head and neck cancer radiation therapy

Reference 32

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Unavailable: canonical work link unavailable.

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Observation 0f0e8865-b703-4ab6-8ab9-a2088b23d116 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 33

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Unavailable: canonical work link unavailable.

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Observation 78345f6f-d6cd-421c-ab56-d2764cb54fa4 · outbound

This paper cites Multimodal Data Integration for Precision Oncology: Challenges and Future Directions.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Multimodal Data Integration for Precision Oncology: Challenges and Future Directions

Reference 34

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Unavailable: canonical work link unavailable.

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Observation 6778c7dc-47bb-4968-8604-6b79907d35b0 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 35

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Unavailable: canonical work link unavailable.

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Observation 3dbd72e1-632a-4098-a0ac-4fae72ed8c5e · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 116b393c-c249-4bac-98ef-f69f208232f8 · outbound

This paper cites an unresolved cited work.

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework Unresolved cited work

Reference 37

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source=pdf_text observed=2026-08-01T19:37:05.713857Z digest=sha256:19fa39a28281d54b09fa8ba7d90a9baceb17610a1ec17739a9ec27c103018721

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