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Citing this Article

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Published on 08.03.17 in Vol 19, No 3 (2017): March

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

Works citing "A Learning Health Care System Using Computer-Aided Diagnosis"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.6663):

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

  1. Ferdousi R, Arab‐Zozani M, Tahamtan I, Rezaei‐Hachesu P, Dehghani M. Attitudes of nurses towards clinical information systems: a systematic review and meta‐analysis. International Nursing Review 2020;
    CrossRef
  2. Garg G, Juneja M. A survey of denoising techniques for multi-parametric prostate MRI. Multimedia Tools and Applications 2019;78(10):12689
    CrossRef
  3. Rider NL, Miao D, Dodds M, Modell V, Modell F, Quinn J, Schwarzwald H, Orange JS. Calculation of a Primary Immunodeficiency “Risk Vital Sign” via Population-Wide Analysis of Claims Data to Aid in Clinical Decision Support. Frontiers in Pediatrics 2019;7
    CrossRef
  4. Schwitzguebel AJ, Jeckelmann C, Gavinio R, Levallois C, Benaïm C, Spechbach H. Differential Diagnosis Assessment in Ambulatory Care With an Automated Medical History–Taking Device: Pilot Randomized Controlled Trial. JMIR Medical Informatics 2019;7(4):e14044
    CrossRef
  5. Ahmad W, Ahmad A, Iqbal A, Hamayun M, Hussain A, Rehman G, Khan S, Khan UU, Khan D, Huang L. Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method. Soft Computing 2019;23(21):10931
    CrossRef
  6. Panigrahi L, Verma K, Singh BK. Ultrasound image segmentation using a novel multi-scale Gaussian kernel fuzzy clustering and multi-scale vector field convolution. Expert Systems with Applications 2019;115:486
    CrossRef
  7. Tuthill JM. Decision Support to Enhance Automated Laboratory Testing by Leveraging Analytical Capabilities. Clinics in Laboratory Medicine 2019;39(2):259
    CrossRef
  8. Ronicke S, Hirsch MC, Türk E, Larionov K, Tientcheu D, Wagner AD. Can a decision support system accelerate rare disease diagnosis? Evaluating the potential impact of Ada DX in a retrospective study. Orphanet Journal of Rare Diseases 2019;14(1)
    CrossRef
  9. Rodgers A, Trinchieri A, Ather MH, Buchholz N. Vision for the future on urolithiasis: research, management, education and training—some personal views. Urolithiasis 2019;47(5):401
    CrossRef
  10. Lake IR, Colón-González FJ, Barker GC, Morbey RA, Smith GE, Elliot AJ. Machine learning to refine decision making within a syndromic surveillance service. BMC Public Health 2019;19(1)
    CrossRef
  11. Yanase J, Triantaphyllou E. The seven key challenges for the future of computer-aided diagnosis in medicine. International Journal of Medical Informatics 2019;129:413
    CrossRef
  12. Price J. Pharmacovigilance in Crisis: Drug Safety at a Crossroads. Clinical Therapeutics 2018;40(5):790
    CrossRef
  13. Keitel K, D'Acremont V. Electronic clinical decision algorithms for the integrated primary care management of febrile children in low-resource settings: review of existing tools. Clinical Microbiology and Infection 2018;24(8):845
    CrossRef
  14. Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJWL. Artificial intelligence in radiology. Nature Reviews Cancer 2018;18(8):500
    CrossRef
  15. Verheij RA, Curcin V, Delaney BC, McGilchrist MM. Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse. Journal of Medical Internet Research 2018;20(5):e185
    CrossRef
  16. Kuiper G, Meijer OLM, Langereis EJ, Wijburg FA. Failure to shorten the diagnostic delay in two ultra-orphan diseases (mucopolysaccharidosis types I and III): potential causes and implications. Orphanet Journal of Rare Diseases 2018;13(1)
    CrossRef