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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11966, 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

Journals

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  4. Sufian A, Ghosh A, Sadiq A, Smarandache F. A Survey on Deep Transfer Learning to Edge Computing for Mitigating the COVID-19 Pandemic. Journal of Systems Architecture 2020;108:101830 View
  5. Choi Y, Kim Y, Chung J, Kim K, Kim H, Park R, Park D. Effect of Age on the Initiation of Biologic Agent Therapy in Patients With Inflammatory Bowel Disease: Korean Common Data Model Cohort Study. JMIR Medical Informatics 2020;8(4):e15124 View
  6. Ma S, Chou W, Chien T, Chow J, Yeh Y, Chou P, Lee H. An App for Detecting Bullying of Nurses Using Convolutional Neural Networks and Web-Based Computerized Adaptive Testing: Development and Usability Study. JMIR mHealth and uHealth 2020;8(5):e16747 View
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  30. Das T, Gohain L, Kakoty N, Malarvili M, Widiyanti P, Kumar G. Hierarchical approach for fusion of electroencephalography and electromyography for predicting finger movements and kinematics using deep learning. Neurocomputing 2023;527:184 View
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  34. Adak A, Pradhan B, Shukla N, Alamri A. Unboxing Deep Learning Model of Food Delivery Service Reviews Using Explainable Artificial Intelligence (XAI) Technique. Foods 2022;11(14):2019 View
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  36. Jameela T, Athota K, Singh N, Gunjan V, Kahali S, Roy S. Deep Learning and Transfer Learning for Malaria Detection. Computational Intelligence and Neuroscience 2022;2022:1 View
  37. Maqsood S, Xu S, Tran S, Garg S, Springer M, Karunanithi M, Mohawesh R. A survey: From shallow to deep machine learning approaches for blood pressure estimation using biosensors. Expert Systems with Applications 2022;197:116788 View
  38. Akbarian S, Nelder M, Russell C, Cawston T, Moreno L, Patel S, Allen V, Dolatabadi E. A Computer Vision Approach to Identifying Ticks Related to Lyme Disease. IEEE Journal of Translational Engineering in Health and Medicine 2022;10:1 View
  39. Peyret R, alSaeed D, Khelifi F, Al-Ghreimil N, Al-Baity H, Bouridane A. Convolutional Neural Network–Based Automatic Classification of Colorectal and Prostate Tumor Biopsies Using Multispectral Imagery: System Development Study. JMIR Bioinformatics and Biotechnology 2022;3(1):e27394 View
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  41. Görtz M, Byczkowski M, Rath M, Schütz V, Reimold P, Gasch C, Simpfendörfer T, März K, Seitel A, Nolden M, Ross T, Mindroc-Filimon D, Michael D, Metzger J, Onogur S, Speidel S, Mündermann L, Fallert J, Müller M, von Knebel Doeberitz M, Teber D, Seitz P, Maier-Hein L, Duensing S, Hohenfellner M. A Platform and Multisided Market for Translational, Software-Defined Medical Procedures in the Operating Room (OP 4.1): Proof-of-Concept Study. JMIR Medical Informatics 2022;10(1):e27743 View
  42. Taimoor N, Rehman S. Reliable and Resilient AI and IoT-Based Personalised Healthcare Services: A Survey. IEEE Access 2022;10:535 View
  43. Ali O, AlAhmad A, Kahtan H. A review of advanced technologies available to improve the healthcare performance during COVID-19 pandemic. Procedia Computer Science 2023;217:205 View
  44. Musa N, Gital A, Aljojo N, Chiroma H, Adewole K, Mojeed H, Faruk N, Abdulkarim A, Emmanuel I, Folawiyo Y, Ogunmodede J, Oloyede A, Olawoyin L, Sikiru I, Katb I. A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram. Journal of Ambient Intelligence and Humanized Computing 2023;14(7):9677 View
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  46. Lee J, Kim S, Kim K, Chai Y, Yu H, Kim S, Choi J, Chung Y, Lee K, Yi K. Assessment of Inter-Institutional Post-Operative Hypoparathyroidism Status Using a Common Data Model. Journal of Clinical Medicine 2021;10(19):4454 View
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  50. Keddy K, Saha S, Kariuki S, Kalule J, Qamar F, Haq Z, Okeke I. Using big data and mobile health to manage diarrhoeal disease in children in low-income and middle-income countries: societal barriers and ethical implications. The Lancet Infectious Diseases 2022;22(5):e130 View
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  54. Parviz M, Brieghel C, Agius R, Niemann C. Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data. Blood Advances 2022;6(12):3716 View
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  56. Selvakanmani S, B A, Devi G, Misra S, R J, Perli S. Deep learning approach to solve image retrieval issues associated with IOT sensors. Measurement: Sensors 2022;24:100458 View
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  58. Ma G, Zhang J, Liu J, Wang L, Yu Y. A Multi-Parameter Fusion Method for Cuffless Continuous Blood Pressure Estimation Based on Electrocardiogram and Photoplethysmogram. Micromachines 2023;14(4):804 View
  59. Lam G, Rish I, Dixon P. Estimating individual minimum calibration for deep-learning with predictive performance recovery: An example case of gait surface classification from wearable sensor gait data. Journal of Biomechanics 2023;154:111606 View
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  61. Li L, Haley L, Boyd A, Bernstam E. Technical/Algorithm, Stakeholder, and Society (TASS) barriers to the application of artificial intelligence in medicine: A systematic review. Journal of Biomedical Informatics 2023;147:104531 View
  62. Xie L, Dou X, Ge T, Han X, Zhang Q, Wang Q, Chen S, He D, Tian W. Deep learning–based identification of spine growth potential on EOS radiographs. European Radiology 2023;34(5):2849 View
  63. García-Ramó K, Sanchez-Catasus C, Winston G. Deep learning in neuroimaging of epilepsy. Clinical Neurology and Neurosurgery 2023;232:107879 View
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  65. Kumar P, Khalid S, Kim H. Prognostics and Health Management of Rotating Machinery of Industrial Robot with Deep Learning Applications—A Review. Mathematics 2023;11(13):3008 View
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Books/Policy Documents

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  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
  15. Chugh A, Jain C. Artificial Intelligence-based Healthcare Systems. View
  16. Demetriou D, Mathabe K, Lolas G, Dlamini Z. Society 5.0 and Next Generation Healthcare. View
  17. Madhu S, Jyothi K, Pravallika S, Sridurga N. Proceedings of the 2nd International Conference on Cognitive and Intelligent Computing. View
  18. Anakal S, Sandhya P. Intelligent Technologies: Concepts, Applications, and Future Directions, Volume 2. View
  19. Seeram E. X-Ray Imaging Systems for Biomedical Engineering Technology. View
  20. Daneshvar H, Boursalie O, Samavi R, Doyle T, Duncan L, Pires P, Sassi R. Artificial Intelligence for Medicine. View
  21. Seeram E, Kanade V. Artificial Intelligence in Medical Imaging Technology. View
  22. Ahuja L, Thakur A. Artificial Intelligence and Speech Technology. View
  23. Settia N, Bhutani M, Saini V. Digitalization and the Transformation of the Healthcare Sector. View