421 related articles for article (PubMed ID: 32783147)
1. Big Data Approaches in Heart Failure Research.
Lanzer JD; Leuschner F; Kramann R; Levinson RT; Saez-Rodriguez J
Curr Heart Fail Rep; 2020 Oct; 17(5):213-224. PubMed ID: 32783147
[TBL] [Abstract][Full Text] [Related]
2. Big-Data Analysis, Cluster Analysis, and Machine-Learning Approaches.
Alonso-Betanzos A; Bolón-Canedo V
Adv Exp Med Biol; 2018; 1065():607-626. PubMed ID: 30051410
[TBL] [Abstract][Full Text] [Related]
3. Omics, big data and machine learning as tools to propel understanding of biological mechanisms and to discover novel diagnostics and therapeutics.
Perakakis N; Yazdani A; Karniadakis GE; Mantzoros C
Metabolism; 2018 Oct; 87():A1-A9. PubMed ID: 30098323
[No Abstract] [Full Text] [Related]
4. Machine Learning and Integrative Analysis of Biomedical Big Data.
Mirza B; Wang W; Wang J; Choi H; Chung NC; Ping P
Genes (Basel); 2019 Jan; 10(2):. PubMed ID: 30696086
[TBL] [Abstract][Full Text] [Related]
5. From cancer big data to treatment: Artificial intelligence in cancer research.
Danishuddin ; Khan S; Kim JJ
J Gene Med; 2024 Jan; 26(1):e3629. PubMed ID: 37940369
[TBL] [Abstract][Full Text] [Related]
6. Decision Support Systems in HF based on Deep Learning Technologies.
Penso M; Solbiati S; Moccia S; Caiani EG
Curr Heart Fail Rep; 2022 Apr; 19(2):38-51. PubMed ID: 35142985
[TBL] [Abstract][Full Text] [Related]
7. Endotyping in Heart Failure - Identifying Mechanistically Meaningful Subtypes of Disease.
Liang LW; Shimada YJ
Circ J; 2021 Aug; 85(9):1407-1415. PubMed ID: 34108305
[TBL] [Abstract][Full Text] [Related]
8. Big data in yeast systems biology.
Yu R; Nielsen J
FEMS Yeast Res; 2019 Nov; 19(7):. PubMed ID: 31603503
[TBL] [Abstract][Full Text] [Related]
9. Big data in IBD: big progress for clinical practice.
Seyed Tabib NS; Madgwick M; Sudhakar P; Verstockt B; Korcsmaros T; Vermeire S
Gut; 2020 Aug; 69(8):1520-1532. PubMed ID: 32111636
[TBL] [Abstract][Full Text] [Related]
10. Data-driven ICU management: Using Big Data and algorithms to improve outcomes.
Carra G; Salluh JIF; da Silva Ramos FJ; Meyfroidt G
J Crit Care; 2020 Dec; 60():300-304. PubMed ID: 32977139
[TBL] [Abstract][Full Text] [Related]
11. Perspective: Big Data and Machine Learning Could Help Advance Nutritional Epidemiology.
Morgenstern JD; Rosella LC; Costa AP; de Souza RJ; Anderson LN
Adv Nutr; 2021 Jun; 12(3):621-631. PubMed ID: 33606879
[TBL] [Abstract][Full Text] [Related]
12. Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.
Passos IC; Ballester PL; Barros RC; Librenza-Garcia D; Mwangi B; Birmaher B; Brietzke E; Hajek T; Lopez Jaramillo C; Mansur RB; Alda M; Haarman BCM; Isometsa E; Lam RW; McIntyre RS; Minuzzi L; Kessing LV; Yatham LN; Duffy A; Kapczinski F
Bipolar Disord; 2019 Nov; 21(7):582-594. PubMed ID: 31465619
[TBL] [Abstract][Full Text] [Related]
13. Revisit of Machine Learning Supported Biological and Biomedical Studies.
Yu XT; Wang L; Zeng T
Methods Mol Biol; 2018; 1754():183-204. PubMed ID: 29536444
[TBL] [Abstract][Full Text] [Related]
14. CLINICAL HETEROGENEITY IN THE AGE OF BIG DATA, ADVANCED ANALYTICS, AND COMPLEXITY THEORY.
Herrington D; Wang Y
Trans Am Clin Climatol Assoc; 2023; 133():56-68. PubMed ID: 37701617
[TBL] [Abstract][Full Text] [Related]
15. Integrative Analysis of Omics Big Data.
Yu XT; Zeng T
Methods Mol Biol; 2018; 1754():109-135. PubMed ID: 29536440
[TBL] [Abstract][Full Text] [Related]
16. Contemporary Applications of Machine Learning for Device Therapy in Heart Failure.
Gautam N; Ghanta SN; Clausen A; Saluja P; Sivakumar K; Dhar G; Chang Q; DeMazumder D; Rabbat MG; Greene SJ; Fudim M; Al'Aref SJ
JACC Heart Fail; 2022 Sep; 10(9):603-622. PubMed ID: 36049812
[TBL] [Abstract][Full Text] [Related]
17. Omics phenotyping in heart failure: the next frontier.
Bayes-Genis A; Liu PP; Lanfear DE; de Boer RA; González A; Thum T; Emdin M; Januzzi JL
Eur Heart J; 2020 Sep; 41(36):3477-3484. PubMed ID: 32337540
[TBL] [Abstract][Full Text] [Related]
18. Big Dreams With Big Data! Use of Clinical Informatics to Inform Biomarker Discovery.
Singh S
Clin Transl Gastroenterol; 2019 Mar; 10(3):e00018. PubMed ID: 30908310
[TBL] [Abstract][Full Text] [Related]
19. Machine Learning Methods Improve Prognostication, Identify Clinically Distinct Phenotypes, and Detect Heterogeneity in Response to Therapy in a Large Cohort of Heart Failure Patients.
Ahmad T; Lund LH; Rao P; Ghosh R; Warier P; Vaccaro B; Dahlström U; O'Connor CM; Felker GM; Desai NR
J Am Heart Assoc; 2018 Apr; 7(8):. PubMed ID: 29650709
[TBL] [Abstract][Full Text] [Related]
20. Machine learning approach to stratify complex heterogeneity of chronic heart failure: A report from the CHART-2 study.
Nakano K; Nochioka K; Yasuda S; Tamori D; Shiroto T; Sato Y; Takaya E; Miyata S; Kawakami E; Ishikawa T; Ueda T; Shimokawa H
ESC Heart Fail; 2023 Jun; 10(3):1597-1604. PubMed ID: 36788745
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
