283 related articles for article (PubMed ID: 33680353)
1. Machine learning applications in microbial ecology, human microbiome studies, and environmental monitoring.
Ghannam RB; Techtmann SM
Comput Struct Biotechnol J; 2021; 19():1092-1107. PubMed ID: 33680353
[TBL] [Abstract][Full Text] [Related]
2. A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems.
Topçuoğlu BD; Lesniak NA; Ruffin MT; Wiens J; Schloss PD
mBio; 2020 Jun; 11(3):. PubMed ID: 32518182
[TBL] [Abstract][Full Text] [Related]
3. Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization.
Cai Y; Gu H; Kenney T
Microbiome; 2017 Aug; 5(1):110. PubMed ID: 28859695
[TBL] [Abstract][Full Text] [Related]
4. A Review of Machine Learning Algorithms for Biomedical Applications.
Binson VA; Thomas S; Subramoniam M; Arun J; Naveen S; Madhu S
Ann Biomed Eng; 2024 May; 52(5):1159-1183. PubMed ID: 38383870
[TBL] [Abstract][Full Text] [Related]
5. Machine Learning Predicts the Presence of 2,4,6-Trinitrotoluene in Sediments of a Baltic Sea Munitions Dumpsite Using Microbial Community Compositions.
Janßen R; Beck AJ; Werner J; Dellwig O; Alneberg J; Kreikemeyer B; Maser E; Böttcher C; Achterberg EP; Andersson AF; Labrenz M
Front Microbiol; 2021; 12():626048. PubMed ID: 34659134
[TBL] [Abstract][Full Text] [Related]
6. Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.
Dutta A; Goldman T; Keating J; Burke E; Williamson N; Dirmeier R; Bowman JS
Microbiol Spectr; 2022 Feb; 10(1):e0190921. PubMed ID: 35138192
[TBL] [Abstract][Full Text] [Related]
7. Can machine learning predict pharmacotherapy outcomes? An application study in osteoporosis.
Lin YT; Chu CY; Hung KS; Lu CH; Bednarczyk EM; Chen HY
Comput Methods Programs Biomed; 2022 Oct; 225():107028. PubMed ID: 35930862
[TBL] [Abstract][Full Text] [Related]
8. Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review.
Buchlak QD; Esmaili N; Leveque JC; Farrokhi F; Bennett C; Piccardi M; Sethi RK
Neurosurg Rev; 2020 Oct; 43(5):1235-1253. PubMed ID: 31422572
[TBL] [Abstract][Full Text] [Related]
9. Microbiome-based classification models for fresh produce safety and quality evaluation.
Liao C; Wang L; Quon G
Microbiol Spectr; 2024 Apr; 12(4):e0344823. PubMed ID: 38445872
[TBL] [Abstract][Full Text] [Related]
10. Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning.
Dully V; Wilding TA; Mühlhaus T; Stoeck T
Comput Struct Biotechnol J; 2021; 19():2256-2268. PubMed ID: 33995917
[TBL] [Abstract][Full Text] [Related]
11. Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.
Wu Z; Zhu M; Kang Y; Leung EL; Lei T; Shen C; Jiang D; Wang Z; Cao D; Hou T
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33313673
[TBL] [Abstract][Full Text] [Related]
12. Comparing quantile regression spline analyses and supervised machine learning for environmental quality assessment at coastal marine aquaculture installations.
Leontidou K; Rubel V; Stoeck T
PeerJ; 2023; 11():e15425. PubMed ID: 37334127
[TBL] [Abstract][Full Text] [Related]
13. Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure.
Qiu H; Luo L; Su Z; Zhou L; Wang L; Chen Y
BMC Med Inform Decis Mak; 2020 May; 20(1):83. PubMed ID: 32357880
[TBL] [Abstract][Full Text] [Related]
14. [Construction of a predictive model for in-hospital mortality of sepsis patients in intensive care unit based on machine learning].
Zhu M; Hu C; He Y; Qian Y; Tang S; Hu Q; Hao C
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul; 35(7):696-701. PubMed ID: 37545445
[TBL] [Abstract][Full Text] [Related]
15. Supervised Machine Learning Enables Geospatial Microbial Provenance.
Bhattacharya C; Tierney BT; Ryon KA; Bhattacharyya M; Hastings JJA; Basu S; Bhattacharya B; Bagchi D; Mukherjee S; Wang L; Henaff EM; Mason CE
Genes (Basel); 2022 Oct; 13(10):. PubMed ID: 36292799
[TBL] [Abstract][Full Text] [Related]
16. Mapping the spatial distribution of the dengue vector
Rahman MS; Pientong C; Zafar S; Ekalaksananan T; Paul RE; Haque U; Rocklöv J; Overgaard HJ
One Health; 2021 Dec; 13():100358. PubMed ID: 34934797
[TBL] [Abstract][Full Text] [Related]
17. Development and internal validation of a machine-learning-developed model for predicting 1-year mortality after fragility hip fracture.
Kitcharanant N; Chotiyarnwong P; Tanphiriyakun T; Vanitcharoenkul E; Mahaisavariya C; Boonyaprapa W; Unnanuntana A
BMC Geriatr; 2022 May; 22(1):451. PubMed ID: 35610589
[TBL] [Abstract][Full Text] [Related]
18. A Machine Learning Approach Reveals a Microbiota Signature for Infection with Mycobacterium avium subsp.
Lee SM; Park HT; Park S; Lee JH; Kim D; Yoo HS; Kim D
Microbiol Spectr; 2023 Feb; 11(1):e0313422. PubMed ID: 36656029
[TBL] [Abstract][Full Text] [Related]
19. Compare the performance of multiple binary classification models in microbial high-throughput sequencing datasets.
Xu N; Zhang Z; Shen Y; Zhang Q; Liu Z; Yu Y; Wang Y; Lei C; Ke M; Qiu D; Lu T; Chen Y; Xiong J; Qian H
Sci Total Environ; 2022 Sep; 837():155807. PubMed ID: 35537509
[TBL] [Abstract][Full Text] [Related]
20. Supervised machine learning to predict reduced depression severity in people with epilepsy through epilepsy self-management intervention.
Camp EJ; Quon RJ; Sajatovic M; Briggs F; Brownrigg B; Janevic MR; Meisenhelter S; Steimel SA; Testorf ME; Kiriakopoulos E; Mazanec MT; Fraser RT; Johnson EK; Jobst BC
Epilepsy Behav; 2022 Feb; 127():108548. PubMed ID: 35042160
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]