FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3156366690> ?p ?o ?g. }

• W3156366690 endingPage "103788" @default.
• W3156366690 startingPage "103788" @default.
• W3156366690 abstract "Clustering analyses in clinical contexts hold promise to improve the understanding of patient phenotype and disease course in chronic and acute clinical medicine. However, work remains to ensure that solutions are rigorous, valid, and reproducible. In this paper, we evaluate best practices for dissimilarity matrix calculation and clustering on mixed-type, clinical data.We simulate clinical data to represent problems in clinical trials, cohort studies, and EHR data, including single-type datasets (binary, continuous, categorical) and 4 data mixtures. We test 5 single distance metrics (Jaccard, Hamming, Gower, Manhattan, Euclidean) and 3 mixed distance metrics (DAISY, Supersom, and Mercator) with 3 clustering algorithms (hierarchical (HC), k-medoids, self-organizing maps (SOM)). We quantitatively and visually validate by Adjusted Rand Index (ARI) and silhouette width (SW). We applied our best methods to two real-world data sets: (1) 21 features collected on 247 patients with chronic lymphocytic leukemia, and (2) 40 features collected on 6000 patients admitted to an intensive care unit.HC outperformed k-medoids and SOM by ARI across data types. DAISY produced the highest mean ARI for mixed data types for all mixtures except unbalanced mixtures dominated by continuous data. Compared to other methods, DAISY with HC uncovered superior, separable clusters in both real-world data sets.Selecting an appropriate mixed-type metric allows the investigator to obtain optimal separation of patient clusters and get maximum use of their data. Superior metrics for mixed-type data handle multiple data types using multiple, type-focused distances. Better subclassification of disease opens avenues for targeted treatments, precision medicine, clinical decision support, and improved patient outcomes." @default.
• W3156366690 created "2021-04-26" @default.
• W3156366690 creator A5011451107 @default.
• W3156366690 creator A5021687717 @default.
• W3156366690 creator A5035224040 @default.
• W3156366690 creator A5087086524 @default.
• W3156366690 date "2021-06-01" @default.
• W3156366690 modified "2023-09-23" @default.
• W3156366690 title "Simulation-derived best practices for clustering clinical data" @default.
• W3156366690 cites W1505191356 @default.
• W3156366690 cites W1513554673 @default.
• W3156366690 cites W1531160357 @default.
• W3156366690 cites W1987971958 @default.
• W3156366690 cites W1991645955 @default.
• W3156366690 cites W2004959076 @default.
• W3156366690 cites W2017885000 @default.
• W3156366690 cites W2022237013 @default.
• W3156366690 cites W2028155376 @default.
• W3156366690 cites W2031192472 @default.
• W3156366690 cites W2033403400 @default.
• W3156366690 cites W2049061656 @default.
• W3156366690 cites W2056884786 @default.
• W3156366690 cites W2057427143 @default.
• W3156366690 cites W2067752346 @default.
• W3156366690 cites W2097349248 @default.
• W3156366690 cites W2103647821 @default.
• W3156366690 cites W2120751691 @default.
• W3156366690 cites W2131994307 @default.
• W3156366690 cites W2133098435 @default.
• W3156366690 cites W2135964318 @default.
• W3156366690 cites W2145680370 @default.
• W3156366690 cites W2149119146 @default.
• W3156366690 cites W2149230623 @default.
• W3156366690 cites W2162151748 @default.
• W3156366690 cites W2396881363 @default.
• W3156366690 cites W2536425004 @default.
• W3156366690 cites W2642176179 @default.
• W3156366690 cites W2767707945 @default.
• W3156366690 cites W2790895082 @default.
• W3156366690 cites W2793628515 @default.
• W3156366690 cites W2802425040 @default.
• W3156366690 cites W2805893819 @default.
• W3156366690 cites W2900404321 @default.
• W3156366690 cites W2900655321 @default.
• W3156366690 cites W2902131578 @default.
• W3156366690 cites W2904756938 @default.
• W3156366690 cites W2944450781 @default.
• W3156366690 cites W2950724928 @default.
• W3156366690 cites W2956342844 @default.
• W3156366690 cites W2978025083 @default.
• W3156366690 cites W2991577140 @default.
• W3156366690 cites W3032612410 @default.
• W3156366690 cites W3091015422 @default.
• W3156366690 cites W3122150487 @default.
• W3156366690 cites W3135366622 @default.
• W3156366690 cites W4235169531 @default.
• W3156366690 cites W4253671195 @default.
• W3156366690 cites W2605774305 @default.
• W3156366690 doi "https://doi.org/10.1016/j.jbi.2021.103788" @default.
• W3156366690 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33862229" @default.
• W3156366690 hasPublicationYear "2021" @default.
• W3156366690 type Work @default.
• W3156366690 sameAs 3156366690 @default.
• W3156366690 citedByCount "7" @default.
• W3156366690 countsByYear W31563666902022 @default.
• W3156366690 countsByYear W31563666902023 @default.
• W3156366690 crossrefType "journal-article" @default.
• W3156366690 hasAuthorship W3156366690A5011451107 @default.
• W3156366690 hasAuthorship W3156366690A5021687717 @default.
• W3156366690 hasAuthorship W3156366690A5035224040 @default.
• W3156366690 hasAuthorship W3156366690A5087086524 @default.
• W3156366690 hasBestOaLocation W31563666902 @default.
• W3156366690 hasConcept C119857082 @default.
• W3156366690 hasConcept C124101348 @default.
• W3156366690 hasConcept C153180895 @default.
• W3156366690 hasConcept C154945302 @default.
• W3156366690 hasConcept C162324750 @default.
• W3156366690 hasConcept C176217482 @default.
• W3156366690 hasConcept C203519979 @default.
• W3156366690 hasConcept C21547014 @default.
• W3156366690 hasConcept C41008148 @default.
• W3156366690 hasConcept C5274069 @default.
• W3156366690 hasConcept C63085389 @default.
• W3156366690 hasConcept C73555534 @default.
• W3156366690 hasConcept C92835128 @default.
• W3156366690 hasConceptScore W3156366690C119857082 @default.
• W3156366690 hasConceptScore W3156366690C124101348 @default.
• W3156366690 hasConceptScore W3156366690C153180895 @default.
• W3156366690 hasConceptScore W3156366690C154945302 @default.
• W3156366690 hasConceptScore W3156366690C162324750 @default.
• W3156366690 hasConceptScore W3156366690C176217482 @default.
• W3156366690 hasConceptScore W3156366690C203519979 @default.
• W3156366690 hasConceptScore W3156366690C21547014 @default.
• W3156366690 hasConceptScore W3156366690C41008148 @default.
• W3156366690 hasConceptScore W3156366690C5274069 @default.
• W3156366690 hasConceptScore W3156366690C63085389 @default.
• W3156366690 hasConceptScore W3156366690C73555534 @default.
• W3156366690 hasConceptScore W3156366690C92835128 @default.

• next