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Paper Citation Record · LEDGER

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data

As of 18 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2506.07092.

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

pith.paper-citation-record.v1
2506.07092 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:47:10.953421Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

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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

62 of 62 outbound references displayed

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External citation measurements

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Outbound references

Observation b6b2e185-9479-45c8-8012-973de73e35d9 · outbound

This paper cites Patient similarity in prediction mod- els based on health data: A scoping review.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Patient similarity in prediction mod- els based on health data: A scoping review

Reference 1

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Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 3

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This paper cites Using dynamic time warping to find patterns in time series, in: In Pro- ceedings of the 3rd International Conference on Knowledge Discovery and Data Mining (AAAIWS’94), p.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Using dynamic time warping to find patterns in time series, in: In Pro- ceedings of the 3rd International Conference on Knowledge Discovery and Data Mining (AAAIWS’94), p

Reference 4

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This paper cites Real-time prediction of mortality, readmission, and length of stay us- ing electronic health record data.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Real-time prediction of mortality, readmission, and length of stay us- ing electronic health record data

Reference 5

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Observation 6e4f09e4-d264-4acf-a7d0-8346aced395e · outbound

This paper cites Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining

Reference 6

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Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 7

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Observation 55fed0b1-7d9a-4c18-934b-4c00fc7a0356 · outbound

This paper cites Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding

Reference 8

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Observation 7d9377c8-28d2-4192-b48e-76aef98f437b · outbound

This paper cites Analysis of microarray data using z-score trans- formation.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Analysis of microarray data using z-score trans- formation

Reference 9

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Observation 9e167e2c-6259-41cd-ae8f-fcb595a9c39f · outbound

This paper cites Risk Prediction with Elec- tronic Health Records: A Deep Learning Approach.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Risk Prediction with Elec- tronic Health Records: A Deep Learning Approach

Reference 10

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Observation 5e7cf051-c31b-4890-bfd7-3ddeec442465 · outbound

This paper cites Introduction to Algorithms, Third Edition.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Introduction to Algorithms, Third Edition

Reference 11

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Observation ce04c526-371a-4f9c-bff6-cca5ee3acadb · outbound

This paper cites A comparative analy- sis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A comparative analy- sis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry

Reference 12

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Observation e9c2da56-1096-499d-9af0-92be5fa5eb2a · outbound

This paper cites Generating evidence based interpretation of hematology screens via anomaly charac- terization.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Generating evidence based interpretation of hematology screens via anomaly charac- terization

Reference 13

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Observation 7e65d47d-f2cf-41f1-bbbc-c053f3d64132 · outbound

This paper cites Statistical comparisons of classifiers over multiple data sets.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Statistical comparisons of classifiers over multiple data sets

Reference 14

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Observation d848c35a-0c9f-41d9-901e-abe57142bffb · outbound

This paper cites Exact indexing of dynamic time warping.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Exact indexing of dynamic time warping

Reference 15

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Observation ff80199b-66cc-4f45-9b5e-73a997e32456 · outbound

This paper cites Tsiklidis, Talid Sinno, S.L.D., 2022.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Tsiklidis, Talid Sinno, S.L.D., 2022

Reference 16

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Observation a4b79a62-92db-498c-aeb2-a551ddfcce9f · outbound

This paper cites Fast subsequence matching in time-series databases.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Fast subsequence matching in time-series databases

Reference 17

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Observation f5694522-9789-4204-a3a0-dc72826df2fb · outbound

This paper cites Intertemporal similarity of economic time series: An application of dynamic time warping.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Intertemporal similarity of economic time series: An application of dynamic time warping

Reference 18

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Observation 2e38ba3b-bd0f-4afb-8aee-ba94070b4d89 · outbound

This paper cites Patient clustering with uncoded text in electronic medical records.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Patient clustering with uncoded text in electronic medical records

Reference 19

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Observation 37b159e6-bdd8-4476-aa5f-d916aff9f7f1 · outbound

This paper cites Survey of clinical data mining applications on big data in health informatics, in: 2013 12th International Conference on Machine Learning and Applica- tions, pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Survey of clinical data mining applications on big data in health informatics, in: 2013 12th International Conference on Machine Learning and Applica- tions, pp

Reference 20

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Observation 5fa33a2b-015f-48f9-9d23-9dce4d653762 · outbound

This paper cites Using participant similarity for the classification of epidemiological data on hepatic steatosis, IEEE.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Using participant similarity for the classification of epidemiological data on hepatic steatosis, IEEE

Reference 21

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Observation 339e47b7-528f-4423-8eae-cec1dd4fb1f9 · outbound

This paper cites Spectral clustering strategies for heterogeneous disease expression data.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Spectral clustering strategies for heterogeneous disease expression data

Reference 22

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Observation 8db1cea4-d098-438b-a098-4552c6d7df2c · outbound

This paper cites Dtw-nn: A novel neural network for time se- ries recognition using dynamic alignment between inputs and weights.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Dtw-nn: A novel neural network for time se- ries recognition using dynamic alignment between inputs and weights

Reference 23

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Observation e518379c-1c61-4d5d-ac63-071678ac6014 · outbound

This paper cites A patient-similarity-based model for diagnostic prediction.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A patient-similarity-based model for diagnostic prediction

Reference 24

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Observation 5ed6dc06-ae7c-43d6-9c21-fc56c250f22d · outbound

This paper cites A novel customer churn prediction model for the telecommunication industry us- ing data transformation methods and feature selection.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A novel customer churn prediction model for the telecommunication industry us- ing data transformation methods and feature selection

Reference 25

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This paper cites Domain wall-grain boundary interactions in polycrystalline Pb(Zr0.7Ti0.3)O3 piezoceramics.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Domain wall-grain boundary interactions in polycrystalline Pb(Zr0.7Ti0.3)O3 piezoceramics

Reference 26

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Observation fba15ce6-1e1b-447a-a6b6-856e598aab50 · outbound

This paper cites Integrated optimisation method for personalised modelling and case studies for medical decision support.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Integrated optimisation method for personalised modelling and case studies for medical decision support

Reference 27

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Observation 15dbced2-eecd-4833-a913-89bb0505863c · outbound

This paper cites Exact indexing of dynamic time warping, in: Proceedings of the 28th International Conference on Very Large Data Bases, VLDB Endowment.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Exact indexing of dynamic time warping, in: Proceedings of the 28th International Conference on Very Large Data Bases, VLDB Endowment

Reference 28

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Observation ac4176f2-873f-49da-a473-cb296bf433a8 · outbound

This paper cites A fast and accurate similarity measure for long time series classification based on local extrema and dynamic time warping.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A fast and accurate similarity measure for long time series classification based on local extrema and dynamic time warping

Reference 29

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Observation 6d34edb8-c05c-4218-920d-590a03dc82b8 · outbound

This paper cites Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis

Reference 30

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Observation 9393119e-2349-45a1-abd4-ffb4185f813d · outbound

This paper cites A ¡i¿k¡/i¿ -nearest neighbors survival probability prediction method.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A ¡i¿k¡/i¿ -nearest neighbors survival probability prediction method

Reference 31

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Observation 153b8f0a-a9b8-4916-9f21-2cea07aa62c9 · outbound

This paper cites Integrate multi-omic data using affinity network fusion (anf) for cancer patient clustering, in: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Integrate multi-omic data using affinity network fusion (anf) for cancer patient clustering, in: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp

Reference 32

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Observation c3feb9e3-995c-406a-95ae-f16958f07317 · outbound

This paper cites An integrated data mining approach to real-time clinical monitoring and deterioration warning, pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data An integrated data mining approach to real-time clinical monitoring and deterioration warning, pp

Reference 33

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raw_fallback, observed 2026-08-07T05:47:14.751338Z

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=2026-08-07T05:47:08.578663Z digest=sha256:64b55b0d5a41b26653d6f07601ebbbacda1ad8f764182dca826c29147aba0f36

Observation a61d84f0-10b1-4840-acb5-360afe0557d8 · outbound

This paper cites Effective patient similarity computa- tion for clinical decision support using time series and static data, pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Effective patient similarity computa- tion for clinical decision support using time series and static data, pp

Reference 34

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T05:47:14.546874Z

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=2026-08-07T05:47:08.607817Z digest=sha256:f163d08e3fcb104e8047c6b7000199070fb4465f394e7e6b7525c83923b662e4

Observation 04e90670-9815-4070-95a3-c34adb0228a3 · outbound

This paper cites Personalized predictive modeling and risk factor identification using patient similarity.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Personalized predictive modeling and risk factor identification using patient similarity

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:19.432172Z

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=2026-08-07T05:47:08.717543Z digest=sha256:6706031626eadbcb734bd41e74b36628b0fc6eaa85afc7f09996b8e238cf1d45

Observation 18e54ea0-08b8-4f9c-b9c8-09c5297651db · outbound

This paper cites Patient similarity networks for preci- sion medicine.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Patient similarity networks for preci- sion medicine

Reference 36

Resolution
verified exact
doi, observed 2026-08-07T05:47:12.092747Z

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=2026-08-07T05:47:08.789747Z digest=sha256:37a18d6d042090f5a0ce6682b647dd5f93d0a4257c9215c53e01f05333ca115c

Observation b862384a-ab4f-49e0-b455-f6733e0d27f9 · outbound

This paper cites Patient similarity for precision medicine: A systematic review.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Patient similarity for precision medicine: A systematic review

Reference 37

Resolution
verified exact
doi, observed 2026-08-07T05:47:11.891992Z

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=2026-08-07T05:47:08.897595Z digest=sha256:92e28f1abb7e6211f333938a15a7adc2add561a4671dde96a3cd7ea99932cb89

Observation a8a1d7b7-8dfe-4961-97dd-69551f0a3aab · outbound

This paper cites New knowledge extraction technique using prob- ability for case-based reasoning: application to medical diagnosis.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data New knowledge extraction technique using prob- ability for case-based reasoning: application to medical diagnosis

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:19.297647Z

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=2026-08-07T05:47:08.935422Z digest=sha256:463f016cdb1bf18e294ec1b1666d6da76ceca6ad4d7f0438d0b564ce0f19a777

Observation 31542074-dbf2-4848-ad3d-6f72e3c9617a · outbound

This paper cites Physionet-MIMICIII.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Physionet-MIMICIII

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:19.144370Z

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=2026-08-07T05:47:09.082320Z digest=sha256:7af036cc1812c44d7914298cc79191f7c801e0b99864f468894b6b4001ea0e90

Observation 1843fb17-8fe3-488a-a0a3-253db2fde2b2 · outbound

This paper cites an unresolved cited work.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 40

Resolution
verified exact
raw_fallback, observed 2026-08-07T05:47:14.382537Z

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=2026-08-07T05:47:09.017882Z digest=sha256:ad9b63cb86a5014be9b75a58c7e750411e728a1b3b78f70c5484b05485d15df5

Observation 85819bf6-820a-419c-811e-092e903b4e9a · outbound

This paper cites netdx: interpretable patient classification using integrated patient similarity networks.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data netdx: interpretable patient classification using integrated patient similarity networks

Reference 41

Resolution
verified exact
doi, observed 2026-08-07T05:47:11.747665Z

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=2026-08-07T05:47:09.376549Z digest=sha256:5e71d7cea6a52afdc73b5eb796e9a081ac308f8fe3149eb30500611bc7c70e3b

Observation 1723f7e2-a716-4fe2-a2b5-869a779b71f0 · outbound

This paper cites Benchmarking deep learn- ing models on large healthcare datasets.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Benchmarking deep learn- ing models on large healthcare datasets

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:19.009697Z

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=2026-08-07T05:47:09.122006Z digest=sha256:9607dc553beb3d384b0ab8c2891322ee790dd701f2cadc8970b3f13e67b748d7

Observation a86a2d8d-a08d-4aad-9320-58880048b3e0 · outbound

This paper cites Privacy-Preserving Customer Churn Prediction Model in the Context of Telecommunication Industry.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Privacy-Preserving Customer Churn Prediction Model in the Context of Telecommunication Industry

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:47:14.172106Z

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=2026-08-07T05:47:09.536699Z digest=sha256:129ac0adcc0bf417ce8c1ec1dbb31de7f3ec052624e1aef44df273df6d8ce5e1

Observation af7c1475-a5f7-4847-8597-5801dbd54496 · outbound

This paper cites Modeling online customer purchase intention behavior applying dif- ferent feature engineering and classification techniques.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Modeling online customer purchase intention behavior applying dif- ferent feature engineering and classification techniques

Reference 44

Resolution
verified exact
doi, observed 2026-08-07T05:47:11.588516Z

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=2026-08-07T05:47:09.582779Z digest=sha256:0e81e247f917b45089fb9c2e1174a0112a6d9996c20aacc0e348d46a342bea40

Observation e19bdb6e-87b9-407e-9fa5-701c2ee73bcd · outbound

This paper cites Toward accurate dynamic time warping in linear time and space.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Toward accurate dynamic time warping in linear time and space

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:18.824973Z

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=2026-08-07T05:47:09.452496Z digest=sha256:5133f00ad11573bb3d0c25669e2312cb9eb9ff856a77e24b3e7c9ba59dc0ca71

Observation 44ee4e2f-9e1d-417a-81b6-7ddbe1675088 · outbound

This paper cites Spark.https://spark.apache.org/.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Spark.https://spark.apache.org/

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:18.676003Z

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=2026-08-07T05:47:09.766203Z digest=sha256:1384eb5fb389338041ba9f230cf7e3012c8563b3fab8d135a1504686123d6281

Observation 70879901-9191-4248-8bb7-8ce38a6f63b7 · outbound

This paper cites Spark.https://www.infoworld.com/article/3236869/what-is-apache-spark-the-big-data-platform-that-crushed-hadoop.html.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Spark.https://www.infoworld.com/article/3236869/what-is-apache-spark-the-big-data-platform-that-crushed-hadoop.html

Reference 47

Resolution
verified exact
raw_fallback, observed 2026-08-07T05:47:14.050039Z

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=2026-08-07T05:47:09.899657Z digest=sha256:2f2efa5a0a0aab4e89fb553925f2c2fd9fd35569ed38d1fce767ea6d68b324b5

Observation 3147cd8e-f045-447b-a80f-4ffb5ae08df3 · outbound

This paper cites Clustering patients ac- cording to health perceptions: Relationships to psychosocial characteristics and medication nonadherence.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Clustering patients ac- cording to health perceptions: Relationships to psychosocial characteristics and medication nonadherence

Reference 48

Resolution
verified exact
doi, observed 2026-08-07T05:47:11.448370Z

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=2026-08-07T05:47:09.716861Z digest=sha256:99c9d2ecb489304f5bdf8f3503c058b474fb65955ffceb6d2128570b5ec233fb

Observation 84268f7d-920c-45e6-ae03-934c2343d6be · outbound

This paper cites Deep patient similarity learning for personalized healthcare.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Deep patient similarity learning for personalized healthcare

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:10.015757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:10.015757Z digest=sha256:1d531f56a22586c3c7b6d3b2f1f419dc530eec4316b623c6e7b07777b667480c

Observation b1f31873-3a4a-432a-8f91-c2e34bbfbb4d · outbound

This paper cites Attention is all you need, in: Proceedings of the 31st International Conference on Neural Information Processing Systems, Curran Associates Inc., Red Hook, NY, USA.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Attention is all you need, in: Proceedings of the 31st International Conference on Neural Information Processing Systems, Curran Associates Inc., Red Hook, NY, USA

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:18.529393Z

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=2026-08-07T05:47:10.093357Z digest=sha256:4de165d359ae142fd18976ba2302b29fd376711984f94609cdf06b527a1bf9d5

Observation 044c2c75-b2fe-47e0-a560-1ac518653a6c · outbound

This paper cites A system for mining temporal physiological data streams for advanced prognostic decision support, IEEE.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A system for mining temporal physiological data streams for advanced prognostic decision support, IEEE

Reference 51

Resolution
verified exact
doi, observed 2026-08-07T05:47:11.294751Z

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=2026-08-07T05:47:09.942272Z digest=sha256:0b3da4d13f0d456a8ca05747f802ca33d45709ef9892c9737aee07297f7596e9

Observation 04bac3a4-f5a9-40aa-87f7-b988b92998b2 · outbound

This paper cites an unresolved cited work.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:18.345957Z

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=2026-08-07T05:47:10.189218Z digest=sha256:b610339c6ec91077b14ea2328cf9e243c2b5c08d332502cb601077ea610419bf

Observation 6421f864-7cd2-4eb1-bb05-9ce0c4c4bcb9 · outbound

This paper cites an unresolved cited work.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:18.195484Z

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=2026-08-07T05:47:10.381665Z digest=sha256:f6ba0f761aa5f7c485b6ea92a4c427a72cddc58f32a6859b43a224eb65680b37

Observation c760423d-7ac8-4167-98e8-9d9a9ba537d9 · outbound

This paper cites Comparing and combining time series trajectories using dynamic time warping.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Comparing and combining time series trajectories using dynamic time warping

Reference 54

Resolution
verified exact
doi, observed 2026-08-07T05:47:11.124937Z

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=2026-08-07T05:47:10.120670Z digest=sha256:723347b41ad3dbcf386256fedaae6be535c413b18c2e87adf966e09b14c7d0c9

Observation b461631b-abf8-4262-81be-86a6621f4e31 · outbound

This paper cites Integrating distance metrics learned from mul- tiple experts and its application in inter-patient similarity assessment, in: SDM.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Integrating distance metrics learned from mul- tiple experts and its application in inter-patient similarity assessment, in: SDM

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:17.865689Z

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=2026-08-07T05:47:10.556921Z digest=sha256:3352a646573ef1b51f9ccf2ad88c078a0bd584b7c21c598e3ca35589fbc1390e

Observation 6a7a8c74-2f2e-4dd3-982d-7d41adac3278 · outbound

This paper cites End-to-End Entity Classification on Multimodal Knowledge Graphs.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data End-to-End Entity Classification on Multimodal Knowledge Graphs

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:10.627461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:10.627461Z digest=sha256:de23d5655eb56c7b1bad95760c9bad777bd5cd196f2e16e5ca47a98a9a9e498a

Observation f5df1872-2f40-4fe1-a1e1-5f5933acdfa9 · outbound

This paper cites Hierarchical Agglomerative Clustering.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Hierarchical Agglomerative Clustering

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:17.671567Z

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=2026-08-07T05:47:10.741689Z digest=sha256:5890c25b3fdc53148a553c8fbde68210267865d7a61f2e39ecefa7725965345b

Observation fd13f8ad-a0a5-409f-ace9-57cc7aa2b775 · outbound

This paper cites Medical prognosis based on patient similarity and expert feedback, in: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Medical prognosis based on patient similarity and expert feedback, in: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:18.011056Z

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=2026-08-07T05:47:10.442503Z digest=sha256:af0349e1ea1d345eeac10246a8e50ad446403f4af2b221a89bd2610b5b7b9317

Observation 11d26a81-a483-4890-86d3-b1528c830176 · outbound

This paper cites Measuring patient similarities via a deep architecture with medical concept embedding, in: 2016 IEEE 16th International Conference on Data Mining (ICDM), pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Measuring patient similarities via a deep architecture with medical concept embedding, in: 2016 IEEE 16th International Conference on Data Mining (ICDM), pp

Reference 60

Resolution
verified exact
raw_fallback, observed 2026-08-07T05:47:13.787428Z

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=2026-08-07T05:47:10.953421Z digest=sha256:7888de6b2a17bf8f102b94a5955fdbe6a69fb0f41c5986ae06425b9e139be43f

Observation d0f673bd-b19d-4c5f-87d7-e861771e4cce · outbound

This paper cites A novel patient similarity prediction model based on semisupervised learning, in: CAIBDA 2022: 2nd International Conference on Artificial Intelligence, Big Data and Algorithms, pp.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data A novel patient similarity prediction model based on semisupervised learning, in: CAIBDA 2022: 2nd International Conference on Artificial Intelligence, Big Data and Algorithms, pp

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:17.507959Z

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=2026-08-07T05:47:10.823082Z digest=sha256:c697d6733fa2302372100ec7b0d364218e22a2a91baad73abc33eef3492c105c

Observation de5024fd-4040-45a8-8cf0-ae1d214e7060 · outbound

This paper cites an unresolved cited work.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 134

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:09.267888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:09.267888Z digest=sha256:051defd338df3e8aa648a2f724940bf22559845e90a690719ed8654138fc46de

Observation aa413780-2e7a-423a-862b-dc59a63ac06a · outbound

This paper cites Nature methods 11.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Nature methods 11

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:10.280743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:10.280743Z digest=sha256:96d91bbcf6106f959c5d98dcc56beb8f9c9d5c223c657fd8a37f515edc2e7e80

Observation d3485834-2fb5-47e8-8740-86c141f7a07c · outbound

This paper cites an unresolved cited work.

Patient Similarity Computation for Clinical Decision Support: An Efficient Use of Data Transformation, Combining Static and Time Series Data Unresolved cited work

Reference 2069

Resolution
verified exact
doi, observed 2026-08-07T05:47:12.248898Z

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=2026-08-07T05:47:08.420203Z digest=sha256:15fafa75d6f277ccc0a7abdf21f134fa1c6c91e5991495416b66861648aa007b

Pith citing papers

No inbound Pith citation observations are available.