Published on in Vol 5, No 3 (2022): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33460, first published .
Evaluating Web-Based Automatic Transcription for Alzheimer Speech Data: Transcript Comparison and Machine Learning Analysis

Evaluating Web-Based Automatic Transcription for Alzheimer Speech Data: Transcript Comparison and Machine Learning Analysis

Evaluating Web-Based Automatic Transcription for Alzheimer Speech Data: Transcript Comparison and Machine Learning Analysis

Journals

  1. Farajzadeh N, Sadeghzadeh N, Ijaz M. NSSI questionnaires revisited: A data mining approach to shorten the NSSI questionnaires. PLOS ONE 2023;18(4):e0284588 View
  2. Hamrick P, Sanborn V, Ostrand R, Gunstad J. Lexical Speech Features of Spontaneous Speech in Older Persons With and Without Cognitive Impairment: Reliability Analysis. JMIR Aging 2023;6:e46483 View
  3. Tang L, Zhang Z, Feng F, Yang L, Li H. Explainable Alzheimer’s Disease Detection Using Linguistic Features from Automatic Speech Recognition. Dementia and Geriatric Cognitive Disorders 2023;52(4):240 View
  4. Al-Hammadi M, Fleyeh H, Åberg A, Halvorsen K, Thomas I. Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review. Journal of Alzheimer's Disease 2024;100(1):1 View
  5. Gao H, Schneider S, Hernandez R, Harris J, Maupin D, Junghaenel D, Kapteyn A, Stone A, Zelinski E, Meijer E, Lee P, Orriens B, Jin H. Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation. JMIR Formative Research 2024;8:e54335 View
  6. König A, Köhler S, Tröger J, Düzel E, Glanz W, Butryn M, Mallick E, Priller J, Altenstein S, Spottke A, Kimmich O, Falkenburger B, Osterrath A, Wiltfang J, Bartels C, Kilimann I, Laske C, Munk M, Roeske S, Frommann I, Hoffmann D, Jessen F, Wagner M, Linz N, Teipel S. Automated remote speech‐based testing of individuals with cognitive decline: Bayesian agreement of transcription accuracy. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 2024;16(4) View
  7. Ding K, Chetty M, Noori Hoshyar A, Bhattacharya T, Klein B. Speech based detection of Alzheimer’s disease: a survey of AI techniques, datasets and challenges. Artificial Intelligence Review 2024;57(12) View
  8. Ghofrani A, Taherdoost H. Biomedical data analytics for better patient outcomes. Drug Discovery Today 2025;30(2):104280 View
  9. Sharafeldeen A, Keowen J, Shaffie A. Machine Learning Approaches for Speech-Based Alzheimer’s Detection: A Comprehensive Survey. Computers 2025;14(2):36 View
  10. Shakeri A, Farmanbar M. Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 2025;17(1) View
  11. Crawford J, Shafiee H. Linguistic changes in spontaneous speech for detecting Parkinson’s disease using large language models. PLOS Digital Health 2025;4(2):e0000757 View
  12. Shankar R, Bundele A, Mukhopadhyay A. A Systematic Review of Natural Language Processing Techniques for Early Detection of Cognitive Impairment. Mayo Clinic Proceedings: Digital Health 2025;3(2):100205 View