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Citing this Article

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Published on 07.03.17 in Vol 19, No 3 (2017): March

This paper is in the following e-collection/theme issue:

Works citing "Exacerbations in Chronic Obstructive Pulmonary Disease: Identification and Prediction Using a Digital Health System"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.7207):

(note that this is only a small subset of citations)

  1. Wang C, Chen X, Du L, Zhan Q, Yang T, Fang Z. Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease. Computer Methods and Programs in Biomedicine 2020;188:105267
    CrossRef
  2. Rodriguez Hermosa JL, Fuster Gomila A, Puente Maestu L, Amado Diago CA, Callejas González FJ, Malo De Molina Ruiz R, Fuentes Ferrer ME, Álvarez Sala-Walther JL, Calle Rubio M. Compliance and Utility of a Smartphone App for the Detection of Exacerbations in Patients With Chronic Obstructive Pulmonary Disease: Cohort Study. JMIR mHealth and uHealth 2020;8(3):e15699
    CrossRef
  3. Battineni G, Sagaro GG, Chinatalapudi N, Amenta F. Applications of Machine Learning Predictive Models in the Chronic Disease Diagnosis. Journal of Personalized Medicine 2020;10(2):21
    CrossRef
  4. Antonelli A, Guilizzoni D, Angelucci A, Melloni G, Mazza F, Stanzi A, Venturino M, Kuller D, Aliverti A. Comparison between the Airgo™ Device and a Metabolic Cart during Rest and Exercise. Sensors 2020;20(14):3943
    CrossRef
  5. van der Burg JM, Aziz NA, Kaptein MC, Breteler MJ, Janssen JH, van Vliet L, Winkeler D, van Anken A, Kasteleyn MJ, Chavannes NH. Long-term effects of telemonitoring on healthcare usage in patients with heart failure or COPD. Clinical eHealth 2020;3:40
    CrossRef
  6. Gonem S, Janssens W, Das N, Topalovic M. Applications of artificial intelligence and machine learning in respiratory medicine. Thorax 2020;75(8):695
    CrossRef
  7. Fan KG, Mandel J, Agnihotri P, Tai-Seale M. Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison. JMIR mHealth and uHealth 2020;8(5):e16147
    CrossRef
  8. Luo G, Stone BL, Koebnick C, He S, Au DH, Sheng X, Murtaugh MA, Sward KA, Schatz M, Zeiger RS, Davidson GH, Nkoy FL. Using Temporal Features to Provide Data-Driven Clinical Early Warnings for Chronic Obstructive Pulmonary Disease and Asthma Care Management: Protocol for a Secondary Analysis. JMIR Research Protocols 2019;8(6):e13783
    CrossRef
  9. Gálvez-Barrón C, Villar-Álvarez F, Ribas J, Formiga F, Chivite D, Boixeda R, Iborra C, Rodríguez-Molinero A. Effort Oxygen Saturation and Effort Heart Rate to Detect Exacerbations of Chronic Obstructive Pulmonary Disease or Congestive Heart Failure. Journal of Clinical Medicine 2019;8(1):42
    CrossRef
  10. Buekers J, Theunis J, De Boever P, Vaes AW, Koopman M, Janssen EV, Wouters EF, Spruit MA, Aerts J. Wearable Finger Pulse Oximetry for Continuous Oxygen Saturation Measurements During Daily Home Routines of Patients With Chronic Obstructive Pulmonary Disease (COPD) Over One Week: Observational Study. JMIR mHealth and uHealth 2019;7(6):e12866
    CrossRef
  11. Lee C, Ho K. Knowledge to action framework for home health monitoring. Healthcare Management Forum 2019;32(4):183
    CrossRef
  12. Soler J, Alves Pegoraro J, Le X, Nguyen D, Grassion L, Antoine R, Guerder A, Gonzalez-Bermejo J. Validation of respiratory rate measurements from remote monitoring device in COPD patients. Respiratory Medicine and Research 2019;76:1
    CrossRef
  13. Wageck B, Cox NS, Holland AE. Recovery Following Acute Exacerbations of Chronic Obstructive Pulmonary Disease – A Review. COPD: Journal of Chronic Obstructive Pulmonary Disease 2019;16(1):93
    CrossRef
  14. Snyder C, Dorsey E, Atreja A. The Best Digital Biomarkers Papers of 2017. Digital Biomarkers 2018;2(2):64
    CrossRef
  15. Tomasic I, Tomasic N, Trobec R, Krpan M, Kelava T. Continuous remote monitoring of COPD patients—justification and explanation of the requirements and a survey of the available technologies. Medical & Biological Engineering & Computing 2018;56(4):547
    CrossRef
  16. Miłkowska-Dymanowska J, Białas AJ, Obrębski W, Górski P, Piotrowski WJ. A pilot study of daily telemonitoring to predict acute exacerbation in chronic obstructive pulmonary disease. International Journal of Medical Informatics 2018;116:46
    CrossRef
  17. Vitacca M, Montini A, Comini L. How will telemedicine change clinical practice in chronic obstructive pulmonary disease?. Therapeutic Advances in Respiratory Disease 2018;12:175346581875477
    CrossRef
  18. Charlton PH, Birrenkott DA, Bonnici T, Pimentel MAF, Johnson AEW, Alastruey J, Tarassenko L, Watkinson PJ, Beale R, Clifton DA. Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review. IEEE Reviews in Biomedical Engineering 2018;11:2
    CrossRef
  19. Morelli D, Bartoloni L, Colombo M, Plans D, Clifton DA. Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device . Healthcare Technology Letters 2018;5(2):59
    CrossRef
  20. Blakey JD, Bender BG, Dima AL, Weinman J, Safioti G, Costello RW. Digital technologies and adherence in respiratory diseases: the road ahead. European Respiratory Journal 2018;52(5):1801147
    CrossRef
  21. Das N, Topalovic M, Janssens W. Artificial intelligence in diagnosis of obstructive lung disease. Current Opinion in Pulmonary Medicine 2018;24(2):117
    CrossRef
  22. Orchard P, Agakova A, Pinnock H, Burton CD, Sarran C, Agakov F, McKinstry B. Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data. Journal of Medical Internet Research 2018;20(9):e263
    CrossRef
  23. Buekers J, De Boever P, Vaes AW, Aerts J, Wouters EFM, Spruit MA, Theunis J. Oxygen saturation measurements in telemonitoring of patients with COPD: a systematic review. Expert Review of Respiratory Medicine 2018;12(2):113
    CrossRef
  24. Farmer A, Williams V, Velardo C, Shah SA, Yu L, Rutter H, Jones L, Williams N, Heneghan C, Price J, Hardinge M, Tarassenko L. Self-Management Support Using a Digital Health System Compared With Usual Care for Chronic Obstructive Pulmonary Disease: Randomized Controlled Trial. Journal of Medical Internet Research 2017;19(5):e144
    CrossRef
  25. Houben-Wilke S, Augustin IM, Wouters BB, Stevens RA, Janssen DJ, Spruit MA, Vanfleteren LE, Franssen FM, Wouters EF. The patient with a complex chronic respiratory disease: a specialist of his own life?. Expert Review of Respiratory Medicine 2017;:1
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.7207)

:
  1. Levin-Zamir D, Parial LL. Encyclopedia of Gerontology and Population Aging. 2020. Chapter 1085-1:1
    CrossRef
  2. Body Sensor Networking, Design and Algorithms. 2020. :157
    CrossRef
  3. do Amaral JLM, de Melo PL. Artificial Intelligence in Precision Health. 2020. :359
    CrossRef
  4. Sumilang CA. Advancing Mobile Learning in Contemporary Educational Spaces. 2019. chapter 4:88
    CrossRef
  5. Nunavath V, Goodwin M, Fidje JT, Moe CE. Engineering Applications of Neural Networks. 2018. Chapter 18:217
    CrossRef