Published on in Vol 9, No 2 (2022): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35325, first published .
Audio Recording Patient-Nurse Verbal Communications in Home Health Care Settings: Pilot Feasibility and Usability Study

Audio Recording Patient-Nurse Verbal Communications in Home Health Care Settings: Pilot Feasibility and Usability Study

Audio Recording Patient-Nurse Verbal Communications in Home Health Care Settings: Pilot Feasibility and Usability Study

Journals

  1. Zolnoori M, Zolnour A, Topaz M. ADscreen: A speech processing-based screening system for automatic identification of patients with Alzheimer's disease and related dementia. Artificial Intelligence in Medicine 2023;143:102624 View
  2. Zolnoori M, Vergez S, Sridharan S, Zolnour A, Bowles K, Kostic Z, Topaz M. Is the patient speaking or the nurse? Automatic speaker type identification in patient–nurse audio recordings. Journal of the American Medical Informatics Association 2023;30(10):1673 View
  3. Zolnoori M, Sridharan S, Zolnour A, Vergez S, McDonald M, Kostic Z, Bowles K, Topaz M. Utilizing patient-nurse verbal communication in building risk identification models: the missing critical data stream in home healthcare. Journal of the American Medical Informatics Association 2024;31(2):435 View
  4. Albert P, Haider F, Luz S. CUSCO: An Unobtrusive Custom Secure Audio-Visual Recording System for Ambient Assisted Living. Sensors 2024;24(5):1506 View
  5. Scroggins J, Topaz M, Song J, Zolnoori M. Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient–nurse verbal communications in home healthcare settings?. Journal of Nursing Scholarship 2024 View
  6. Zolnoori M, Vergez S, Xu Z, Esmaeili E, Zolnour A, Anne Briggs K, Scroggins J, Hosseini Ebrahimabad S, Noble J, Topaz M, Bakken S, Bowles K, Spens I, Onorato N, Sridharan S, McDonald M. Decoding disparities: evaluating automatic speech recognition system performance in transcribing Black and White patient verbal communication with nurses in home healthcare. JAMIA Open 2024;7(4) View
  7. Zolnoori M, Zolnour A, Vergez S, Sridharan S, Spens I, Topaz M, Noble J, Bakken S, Hirschberg J, Bowles K, Onorato N, McDonald M. Beyond electronic health record data: leveraging natural language processing and machine learning to uncover cognitive insights from patient-nurse verbal communications. Journal of the American Medical Informatics Association 2024 View