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For: Gaubert S, Houot M, Raimondo F, Ansart M, Corsi MC, Naccache L, Sitt JD, Habert MO, Dubois B, De Vico Fallani F, Durrleman S, Epelbaum S; INSIGHT-preAD study group. A machine learning approach to screen for preclinical Alzheimer's disease. Neurobiol Aging 2021;105:205-16. [PMID: 34102381 DOI: 10.1016/j.neurobiolaging.2021.04.024] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Öhman F, Hassenstab J, Berron D, Schöll M, Papp KV. Current advances in digital cognitive assessment for preclinical Alzheimer's disease. Alzheimers Dement (Amst) 2021;13:e12217. [PMID: 34295959 DOI: 10.1002/dad2.12217] [Reference Citation Analysis]
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4 Khosla A, Khandnor P, Chand T. Automated diagnosis of depression from EEG signals using traditional and deep learning approaches: A comparative analysis. Biocybernetics and Biomedical Engineering 2022;42:108-42. [DOI: 10.1016/j.bbe.2021.12.005] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Wu Y, Wang Y, Zhang L, Liu L, Pan Y, Su T, Liao X, Shu H, Kang M, Ying P, Xu S, Shao Y. Regional Homogeneity in Patients With Mild Cognitive Impairment: A Resting-State Functional Magnetic Resonance Imaging Study. Front Aging Neurosci 2022;14:877281. [DOI: 10.3389/fnagi.2022.877281] [Reference Citation Analysis]
6 Moral-Rubio C, Balugo P, Fraile-Pereda A, Pytel V, Fernández-Romero L, Delgado-Alonso C, Delgado-Álvarez A, Matias-Guiu J, Matias-Guiu JA, Ayala JL. Application of Machine Learning to Electroencephalography for the Diagnosis of Primary Progressive Aphasia: A Pilot Study. Brain Sci 2021;11:1262. [PMID: 34679327 DOI: 10.3390/brainsci11101262] [Reference Citation Analysis]