Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49147, first published .
A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study

A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study

A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study

Journals

  1. Tascedda S, Sarti P, Rivi V, Guerrera C, Platania G, Santagati M, Caraci F, Blom J. Advanced AI techniques for classifying Alzheimer’s disease and mild cognitive impairment. Frontiers in Aging Neuroscience 2024;16 View
  2. Yang P, Xiao X, Li Y, Cao X, Li M, Liu X, Gong L, Liu F, Dai X. Development and validation of a convenient dementia risk prediction tool for diabetic population: A large and longitudinal machine learning cohort study. Journal of Affective Disorders 2025;380:298 View
  3. Qi W, Zhu X, Wang B, Shi Y, Dong C, Shen S, Li J, Zhang K, He Y, Zhao M, Yao S, Dong Y, Shen H, Kang J, Lu X, Jiang G, Boots L, Fu H, Pan L, Chen H, Yan Z, Xing G, Cao S. Alzheimer’s disease digital biomarkers multidimensional landscape and AI model scoping review. npj Digital Medicine 2025;8(1) View