These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
150 related articles for article (PubMed ID: 38269642)
1. Improving reporting standards for phenotyping algorithm in biomedical research: 5 fundamental dimensions. Wei WQ; Rowley R; Wood A; MacArthur J; Embi PJ; Denaxas S J Am Med Inform Assoc; 2024 Apr; 31(4):1036-1041. PubMed ID: 38269642 [TBL] [Abstract][Full Text] [Related]
2. Machine learning approaches for electronic health records phenotyping: a methodical review. Yang S; Varghese P; Stephenson E; Tu K; Gronsbell J J Am Med Inform Assoc; 2023 Jan; 30(2):367-381. PubMed ID: 36413056 [TBL] [Abstract][Full Text] [Related]
3. Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries. Hong N; Wen A; Stone DJ; Tsuji S; Kingsbury PR; Rasmussen LV; Pacheco JA; Adekkanattu P; Wang F; Luo Y; Pathak J; Liu H; Jiang G J Biomed Inform; 2019 Nov; 99():103310. PubMed ID: 31622801 [TBL] [Abstract][Full Text] [Related]
4. Weakly Semi-supervised phenotyping using Electronic Health records. Nogues IE; Wen J; Lin Y; Liu M; Tedeschi SK; Geva A; Cai T; Hong C J Biomed Inform; 2022 Oct; 134():104175. PubMed ID: 36064111 [TBL] [Abstract][Full Text] [Related]
5. A collaborative approach to developing an electronic health record phenotyping algorithm for drug-induced liver injury. Overby CL; Pathak J; Gottesman O; Haerian K; Perotte A; Murphy S; Bruce K; Johnson S; Talwalkar J; Shen Y; Ellis S; Kullo I; Chute C; Friedman C; Bottinger E; Hripcsak G; Weng C J Am Med Inform Assoc; 2013 Dec; 20(e2):e243-52. PubMed ID: 23837993 [TBL] [Abstract][Full Text] [Related]
7. MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health record. Ahuja Y; Zou Y; Verma A; Buckeridge D; Li Y J Biomed Inform; 2022 Oct; 134():104190. PubMed ID: 36058522 [TBL] [Abstract][Full Text] [Related]
8. Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods. Richesson RL; Sun J; Pathak J; Kho AN; Denny JC Artif Intell Med; 2016 Jul; 71():57-61. PubMed ID: 27506131 [TBL] [Abstract][Full Text] [Related]
9. The use of electronic health records for psychiatric phenotyping and genomics. Smoller JW Am J Med Genet B Neuropsychiatr Genet; 2018 Oct; 177(7):601-612. PubMed ID: 28557243 [TBL] [Abstract][Full Text] [Related]
10. High-throughput phenotyping with temporal sequences. Estiri H; Strasser ZH; Murphy SN J Am Med Inform Assoc; 2021 Mar; 28(4):772-781. PubMed ID: 33313899 [TBL] [Abstract][Full Text] [Related]
12. Methods for enhancing the reproducibility of biomedical research findings using electronic health records. Denaxas S; Direk K; Gonzalez-Izquierdo A; Pikoula M; Cakiroglu A; Moore J; Hemingway H; Smeeth L BioData Min; 2017; 10():31. PubMed ID: 28912836 [TBL] [Abstract][Full Text] [Related]
13. Automated feature selection of predictors in electronic medical records data. Gronsbell J; Minnier J; Yu S; Liao K; Cai T Biometrics; 2019 Mar; 75(1):268-277. PubMed ID: 30353541 [TBL] [Abstract][Full Text] [Related]
14. Accuracy of phenotyping chronic rhinosinusitis in the electronic health record. Hsu J; Pacheco JA; Stevens WW; Smith ME; Avila PC Am J Rhinol Allergy; 2014; 28(2):140-4. PubMed ID: 24717952 [TBL] [Abstract][Full Text] [Related]
15. Concept libraries for automatic electronic health record based phenotyping: A review. Almowil ZA; Zhou SM; Brophy S Int J Popul Data Sci; 2021 Jun; 6(1):1362. PubMed ID: 34189274 [TBL] [Abstract][Full Text] [Related]
16. Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium. Pathak J; Bailey KR; Beebe CE; Bethard S; Carrell DC; Chen PJ; Dligach D; Endle CM; Hart LA; Haug PJ; Huff SM; Kaggal VC; Li D; Liu H; Marchant K; Masanz J; Miller T; Oniki TA; Palmer M; Peterson KJ; Rea S; Savova GK; Stancl CR; Sohn S; Solbrig HR; Suesse DB; Tao C; Taylor DP; Westberg L; Wu S; Zhuo N; Chute CG J Am Med Inform Assoc; 2013 Dec; 20(e2):e341-8. PubMed ID: 24190931 [TBL] [Abstract][Full Text] [Related]
17. Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms. Albers DJ; Elhadad N; Claassen J; Perotte R; Goldstein A; Hripcsak G J Biomed Inform; 2018 Feb; 78():87-101. PubMed ID: 29369797 [TBL] [Abstract][Full Text] [Related]
18. Scalable relevance ranking algorithm via semantic similarity assessment improves efficiency of medical chart review. Cai T; He Z; Hong C; Zhang Y; Ho YL; Honerlaw J; Geva A; Ayakulangara Panickan V; King A; Gagnon DR; Gaziano M; Cho K; Liao K; Cai T J Biomed Inform; 2022 Aug; 132():104109. PubMed ID: 35660521 [TBL] [Abstract][Full Text] [Related]
19. PIAT: An Evolutionarily Intelligent System for Deep Phenotyping of Chinese Electronic Health Records. Deng L; Zhang X; Yang T; Liu M; Chen L; Jiang T IEEE J Biomed Health Inform; 2022 Aug; 26(8):4142-4152. PubMed ID: 35609107 [TBL] [Abstract][Full Text] [Related]
20. Feasibility of Using EN 13606 Clinical Archetypes for Defining Computable Phenotypes. Tapuria A; Kalra D; Curcin V Stud Health Technol Inform; 2020 Jun; 270():228-232. PubMed ID: 32570380 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]