363 related articles for article (PubMed ID: 30279002)
21. What is Machine Learning? A Primer for the Epidemiologist.
Bi Q; Goodman KE; Kaminsky J; Lessler J
Am J Epidemiol; 2019 Dec; 188(12):2222-2239. PubMed ID: 31509183
[TBL] [Abstract][Full Text] [Related]
22. Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements.
McLeod A; Bochniewicz EM; Lum PS; Holley RJ; Emmer G; Dromerick AW
Arch Phys Med Rehabil; 2016 Feb; 97(2):224-31. PubMed ID: 26435302
[TBL] [Abstract][Full Text] [Related]
23. Wearable Sensor Data to Track Subject-Specific Movement Patterns Related to Clinical Outcomes Using a Machine Learning Approach.
Kobsar D; Ferber R
Sensors (Basel); 2018 Aug; 18(9):. PubMed ID: 30150560
[TBL] [Abstract][Full Text] [Related]
24. Machine learning methods to support personalized neuromusculoskeletal modelling.
Saxby DJ; Killen BA; Pizzolato C; Carty CP; Diamond LE; Modenese L; Fernandez J; Davico G; Barzan M; Lenton G; da Luz SB; Suwarganda E; Devaprakash D; Korhonen RK; Alderson JA; Besier TF; Barrett RS; Lloyd DG
Biomech Model Mechanobiol; 2020 Aug; 19(4):1169-1185. PubMed ID: 32676934
[TBL] [Abstract][Full Text] [Related]
25. Human Activity Recognition from Body Sensor Data using Deep Learning.
Hassan MM; Huda S; Uddin MZ; Almogren A; Alrubaian M
J Med Syst; 2018 Apr; 42(6):99. PubMed ID: 29663090
[TBL] [Abstract][Full Text] [Related]
26. Biomechanics: an integral part of sport science and sport medicine.
Elliott B
J Sci Med Sport; 1999 Dec; 2(4):299-310. PubMed ID: 10710008
[TBL] [Abstract][Full Text] [Related]
27. Measuring Functional Arm Movement after Stroke Using a Single Wrist-Worn Sensor and Machine Learning.
Bochniewicz EM; Emmer G; McLeod A; Barth J; Dromerick AW; Lum P
J Stroke Cerebrovasc Dis; 2017 Dec; 26(12):2880-2887. PubMed ID: 28781056
[TBL] [Abstract][Full Text] [Related]
28. Enhancing cricket batting skill: implications for biomechanics and skill acquisition research and practice.
Portus MR; Farrow D
Sports Biomech; 2011 Nov; 10(4):294-305. PubMed ID: 22303782
[TBL] [Abstract][Full Text] [Related]
29. Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View.
Luo W; Phung D; Tran T; Gupta S; Rana S; Karmakar C; Shilton A; Yearwood J; Dimitrova N; Ho TB; Venkatesh S; Berk M
J Med Internet Res; 2016 Dec; 18(12):e323. PubMed ID: 27986644
[TBL] [Abstract][Full Text] [Related]
30. Machine Learning Methodology in a System Applying the Adaptive Strategy for Teaching Human Motions.
Wójcik K; Piekarczyk M
Sensors (Basel); 2020 Jan; 20(1):. PubMed ID: 31935910
[TBL] [Abstract][Full Text] [Related]
31. Cricket fast bowling detection in a training setting using an inertial measurement unit and machine learning.
McGrath JW; Neville J; Stewart T; Cronin J
J Sports Sci; 2019 Jun; 37(11):1220-1226. PubMed ID: 30543315
[TBL] [Abstract][Full Text] [Related]
32. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK
Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719
[TBL] [Abstract][Full Text] [Related]
33. Scientific basis of the OCRA method for risk assessment of biomechanical overload of upper limb, as preferred method in ISO standards on biomechanical risk factors.
Colombini D; Occhipinti E
Scand J Work Environ Health; 2018 Jul; 44(4):436-438. PubMed ID: 29961081
[TBL] [Abstract][Full Text] [Related]
34. From machine learning to deep learning: progress in machine intelligence for rational drug discovery.
Zhang L; Tan J; Han D; Zhu H
Drug Discov Today; 2017 Nov; 22(11):1680-1685. PubMed ID: 28881183
[TBL] [Abstract][Full Text] [Related]
35. The effectiveness of internet-based e-learning on clinician behavior and patient outcomes: a systematic review protocol.
Sinclair P; Kable A; Levett-Jones T
JBI Database System Rev Implement Rep; 2015 Jan; 13(1):52-64. PubMed ID: 26447007
[TBL] [Abstract][Full Text] [Related]
36. Detection of Talking in Respiratory Signals: A Feasibility Study Using Machine Learning and Wearable Textile-Based Sensors.
Ejupi A; Menon C
Sensors (Basel); 2018 Jul; 18(8):. PubMed ID: 30065177
[TBL] [Abstract][Full Text] [Related]
37. The use of machine learning in paediatric nutrition.
Young A; Johnson MJ; Beattie RM
Curr Opin Clin Nutr Metab Care; 2024 May; 27(3):290-296. PubMed ID: 38294876
[TBL] [Abstract][Full Text] [Related]
38. Nurses "Seeing Forest for the Trees" in the Age of Machine Learning: Using Nursing Knowledge to Improve Relevance and Performance.
Kwon JY; Karim ME; Topaz M; Currie LM
Comput Inform Nurs; 2019 Apr; 37(4):203-212. PubMed ID: 30688670
[TBL] [Abstract][Full Text] [Related]
39. Prediction of sepsis patients using machine learning approach: A meta-analysis.
Islam MM; Nasrin T; Walther BA; Wu CC; Yang HC; Li YC
Comput Methods Programs Biomed; 2019 Mar; 170():1-9. PubMed ID: 30712598
[TBL] [Abstract][Full Text] [Related]
40. Next-Generation Machine Learning for Biological Networks.
Camacho DM; Collins KM; Powers RK; Costello JC; Collins JJ
Cell; 2018 Jun; 173(7):1581-1592. PubMed ID: 29887378
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
