Paper Citation Record · LEDGER

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data

As of 10 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2508.20133.

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

pith.paper-citation-record.v1
2508.20133 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:58:15.153878Z

measured 23 of 23 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

23 of 23 outbound references displayed

verified exact0
verified fuzzy21
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 37b112a5-53ae-4251-bc20-f4b546899623 · outbound

This paper cites Arik and Tomas Pfister.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Arik and Tomas Pfister

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.532964Z

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.

Observation b6c4ed45-dc34-4583-83a4-54046241733e · outbound

This paper cites Bates, Suchi Saria, Lucila Ohno-Machado, Nigam Shah, and Gabriel Escobar.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Bates, Suchi Saria, Lucila Ohno-Machado, Nigam Shah, and Gabriel Escobar

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.518693Z

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.

Observation 59f0b2ef-5d08-4223-8aa9-f4bdff039376 · outbound

This paper cites Random forests.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Random forests

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.504397Z

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.

Observation f4d8c638-90fe-44ac-9ac2-14e7121aee31 · outbound

This paper cites Xgboost: A scalable tree boosting system.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Xgboost: A scalable tree boosting system

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.490128Z

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.

Observation 4a8008ee-c451-4ec0-bccc-71fe13eaa0e1 · outbound

This paper cites Recent advances and clin- ical applications of deep learning in medical image analysis.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Recent advances and clin- ical applications of deep learning in medical image analysis

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.474923Z

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.

Observation 134a8d7b-117c-422b-90c1-6d93d8f65fe9 · outbound

This paper cites Chronic kidney disease stage identification in hiv infected patients using machine learning.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Chronic kidney disease stage identification in hiv infected patients using machine learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.459774Z

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.

Observation cc6affea-e3ed-42b7-97c7-cee1a1cf4c16 · outbound

This paper cites Metrics for Multi-Class Classification: an Overview.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Metrics for Multi-Class Classification: an Overview

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T15:58:15.081418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39fbd612-71f0-4617-8b25-214bbeac32d6 · outbound

This paper cites Premature age-related comorbidi- ties among hiv-infected persons compared with the gen- eral population.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Premature age-related comorbidi- ties among hiv-infected persons compared with the gen- eral population

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.444742Z

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.

Observation 5a475a40-3d49-4233-a0ef-e1028363adf7 · outbound

This paper cites Guaraldi et al.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Guaraldi et al

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.429957Z

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.

Observation e800d8dc-77e1-4e96-95a5-650cf10e4dd5 · outbound

This paper cites Global aids update 2023, 2023.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Global aids update 2023, 2023

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.415428Z

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.

Observation 600c704e-9c39-4920-8294-5b22e36ab22a · outbound

This paper cites Light- gbm: A highly efficient gradient boosting decision tree.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Light- gbm: A highly efficient gradient boosting decision tree

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.400638Z

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.

Observation d23c8931-6632-49eb-a615-f8ef217aeca3 · outbound

This paper cites Gordon, and Aldo A.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Gordon, and Aldo A

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.385672Z

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.

Observation 572e33f5-e518-49de-bc17-80f0ea15a58c · outbound

This paper cites An efficient approach to estimate the risk of coronary artery disease for people living with hiv us- ing machine-learning-based retinal image analysis.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data An efficient approach to estimate the risk of coronary artery disease for people living with hiv us- ing machine-learning-based retinal image analysis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.369259Z

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.

Observation b42f8446-d045-4d5a-8c1c-b19673990d8f · outbound

This paper cites Applied Logistic Regression Analysis.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Applied Logistic Regression Analysis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.352322Z

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.

Observation 6f242b20-2865-4952-93ee-32ab326b4376 · outbound

This paper cites Kidd, and Joel T.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Kidd, and Joel T

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.336950Z

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.

Observation 5669fa24-3cb4-46de-8ac8-cae1b3ce6ee2 · outbound

This paper cites Dai, et al.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Dai, et al

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.322039Z

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.

Observation 3148631f-f55f-49e7-9cfd-33fe61bbdbf4 · outbound

This paper cites Stratification for multi-label data.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Stratification for multi-label data

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.306048Z

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.

Observation 94ef0cc0-6818-4ddf-854b-2a926e7c93b0 · outbound

This paper cites Deep ehr: a survey of recent advances in deep learning techniques for electronic health record (ehr) analysis.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Deep ehr: a survey of recent advances in deep learning techniques for electronic health record (ehr) analysis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.289746Z

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.

Observation cf5dfda5-a098-468f-9339-9343d57986e0 · outbound

This paper cites Deep ehr: A survey of recent advances in deep learning techniques for electronic health record (ehr) analy- sis.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Deep ehr: A survey of recent advances in deep learning techniques for electronic health record (ehr) analy- sis

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.271256Z

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.

Observation a5327916-abc9-4b10-b3c8-daf4f594b3af · outbound

This paper cites Investigating the impact of data normalization on classification performance.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Investigating the impact of data normalization on classification performance

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.255244Z

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.

Observation c00e79af-ada1-4401-8447-a34e9e0f8663 · outbound

This paper cites an unresolved cited work.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:58:15.238931Z

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.

Observation 5f697884-4fb4-44bd-bb1b-9a229d539ed7 · outbound

This paper cites An interpretable mortality prediction model for covid-19 patients.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data An interpretable mortality prediction model for covid-19 patients

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.223453Z

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.

Observation f46bb3a4-e4ec-4f4b-83db-cdb36a20f5bb · outbound

This paper cites Machine learning-based prognostic prediction for hospitalized hiv/aids patients with cryptococcus infection in guangxi, china.

Proactive HIV Care: AI-Based Comorbidity Prediction from Routine EHR Data Machine learning-based prognostic prediction for hospitalized hiv/aids patients with cryptococcus infection in guangxi, china

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:58:15.207929Z

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.

Pith citing papers

No inbound Pith citation observations are available.