Year: 2022
Type: article
Abstract: Alzheimer's disease is still a field of research with lots of open questions. The complexity of the disease prevents the early diagnosis before visible symptoms regarding the individual's cognitive capabilities occur. This research presents an in-depth analysis of a huge data set encompassing medical, cognitive and lifestyle's measurements from more than 12,000 individuals. Several hypothesis were established whose validity has been questioned considering the obtained results. The importance of appropriate experimental design is highly stressed in the research. Thus, a sequence of methods for handling missing data, redundancy, data imbalance, and correlation analysis have been applied for appropriate preprocessing of the data set, and consequently XGBoost model has been trained and evaluated with special attention to the hyperparameters tuning. The model was explained by using the Shapley values produced by the SHAP method. XGBoost produced a f1-score of 0.84 and as such is considered to be highly competitive among those published in the literature. This achievement, however, was not the main contribution of this paper. This research's goal was to perform global and local interpretability of the intelligent model and derive valuable conclusions over the established hypothesis. Those methods led to a single scheme which presents either positive, or, negative influence of the values of each of the features whose importance has been confirmed by means of Shapley values. This scheme might be considered as additional source of knowledge for the physicians and other experts whose concern is the exact diagnosis of early stage of Alzheimer's disease. The conclusions derived from the intelligent model's data-driven interpretability confronted all the established hypotheses. This research clearly showed the importance of explainable Machine learning approach that opens the black box and clearly unveils the relationships among the features and the diagnoses.
Source: Scientific Reports
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,190
Funders: U.S. Department of Defense, Foundation for the National Institutes of Health, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, F. Hoffmann-La Roche, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Eisai, Javna Agencija za Raziskovalno Dejavnost RS, Servier, H. Lundbeck A/S, IXICO, National Institutes of Health, Genentech, Horizon 2020 Framework Programme, Canadian Institutes of Health Research, Horizon 2020, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering
Awards: G1012222616, G1187842101, G1298807586, G1554142629, G1593117279, G1650819308, G1693528767, G1823308732, G1880935189, G2100670906, G2105457377, G2152643862, G2189010064, G2340207221, Mr-BEC: Modern approaches for Benchmarking in Evolutionary Computation, G2423387114, G2471646051, G2522063444, G2835601961, G29951154, G3130427885, G3131374986, G3146424788, G3216574877, G3553156159, G3705772492, G3710456697, G3752451908, G3870774570, Communities on Food Consumer Science, G3908963977, G3966393351, G4119534169, G4141766493, G43180419, G434337789, G4401988282, G4415536302, G4475667458, G4501223628, G4800177743, G4860885537, G5014702639, G5207404921, G5209990037, G528601746, G5324093878, G5365730499, EFFECTS OF TRAUMATIC BRAIN INJURY (TBI) AND POST TRAUMATIC STRESS DISORDER (PTSD) ON ALZHEIMER'S DISEASE (AD) IN VETERANS USING IMAGING AND BIOMARKERS IN THE AD NEUROIMAGING INITIATIVE (ADNI)", G5654639750, Alzheimer's Disease Neuroimaging Initiative, G5740349702, G5850682332, G613619302, G6173816828, G6210868510, G6305660231, G6371410416, G6412110892, G6447063303, G6719828067, G6743419478, G6792506723, G6899163935, G6948409098, G72415811, G7298697282, G7414321945, G764699806, G7799614282, G781725486, Computer Structures and Systems, Food Nutrition Security Cloud, G8228018387, G8281378126, G839208290, G8789742418, G8852128998, G8895907669, G8897063270, G8957659042, G9000074849, G9000122335, G920654007
OpenAlex ID: W4224257823