Published on in Vol 7 , No 8 (2019) :August

Preprints (earlier versions) of this paper are available at, first published .
Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations

Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations

Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations


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Books/Policy Documents

  1. Mathew P, Pillai A. Enabling AI Applications in Data Science. View
  2. . Cloud-Based M-Health Systems for Vein Image Enhancement and Feature Extraction. View
  3. Kose U, Deperlioglu O, Alzubi J, Patrut B. Deep Learning for Medical Decision Support Systems. View
  4. Mahapatra D, Ray R, Dash S. Technical Advancements of Machine Learning in Healthcare. View
  5. Gaur N, Dharwadkar R, Thomas J. Deep Learning for Targeted Treatments. View
  6. Dargad S, Thakkar P, Giri S. Computing Science, Communication and Security. View
  7. Mac T. Proceedings of 10th International Conference on Mechatronics and Control Engineering. View
  8. Kumar S, Pooja , Kumar S, Veer K. Machine Learning Algorithms for Signal and Image Processing. View
  9. Nova S, Rahman M, Hosen A. Rhythms in Healthcare. View
  10. Shastry K, Sanjay H, Lakshmi M, Preetham N. Bioinformatics and Medical Applications. View
  11. Aditya Shastry K, Sanjay H, Lakshmi M, Preetham N. Blockchain and Deep Learning. View
  12. Mishra A, Mohapatra S, Bisoy S. Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis. View
  13. Olaniyan O, Adetunji C, Adeyomoye O, Dare A, Adeniyi M, Enoch A. Artificial Intelligence for Neurological Disorders. View
  14. Bishi D, Padhi P, Panigrahi C, Pati B, Rath C. Computational Intelligence in Cancer Diagnosis. View