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% Source: https://alzhub.org/research?category=digital&journal=Scientific+Reports
% 20 entries, in the order the page lists them. Built from alzhub.org's own records.
% 0 entries have no readable author in the source record and carry no author field.

@article{elsappagh2021-33514817,
  author  = {El-Sappagh, S. and Alonso, J. M. and Islam, S. M. R. and Sultan, A. M. and Kwak, K. S.},
  title   = {{A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease}},
  journal = {Scientific reports},
  year    = {2021},
  doi     = {10.1038/s41598-021-82098-3},
  pmid    = {33514817},
  url     = {https://doi.org/10.1038/s41598-021-82098-3}
}

@article{spooner2020-33230128,
  author  = {Spooner, A. and Chen, E. and Sowmya, A. and Sachdev, P. and Kochan, N. A. and Trollor, J. and Brodaty, H.},
  title   = {{A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction}},
  journal = {Scientific reports},
  year    = {2020},
  doi     = {10.1038/s41598-020-77220-w},
  pmid    = {33230128},
  url     = {https://doi.org/10.1038/s41598-020-77220-w}
}

@article{lee2018-29515131,
  author  = {Lee, J. S. and Kim, C. and Shin, J. H. and Cho, H. and Shin, D. S. and Kim, N. and Kim, H. J. and Kim, Y. and others},
  title   = {{Machine Learning-based Individual Assessment of Cortical Atrophy Pattern in Alzheimer's Disease Spectrum: Development of the Classifier and Longitudinal Evaluation}},
  journal = {Scientific reports},
  year    = {2018},
  doi     = {10.1038/s41598-018-22277-x},
  pmid    = {29515131},
  url     = {https://doi.org/10.1038/s41598-018-22277-x}
}

@article{gomezramirez2020-33244011,
  author  = {Gómez-Ramírez, J. and Ávila-Villanueva, M. and MÁ, Fernández-Blázquez},
  title   = {{Selecting the most important self-assessed features for predicting conversion to mild cognitive impairment with random forest and permutation-based methods}},
  journal = {Scientific reports},
  year    = {2020},
  doi     = {10.1038/s41598-020-77296-4},
  pmid    = {33244011},
  url     = {https://doi.org/10.1038/s41598-020-77296-4}
}

@article{alatrany2024-38302557,
  author  = {Alatrany, A. S. and Khan, W. and Hussain, A. and Kolivand, H. and Al-Jumeily, D.},
  title   = {{An explainable machine learning approach for Alzheimer's disease classification}},
  journal = {Scientific reports},
  year    = {2024},
  doi     = {10.1038/s41598-024-51985-w},
  pmid    = {38302557},
  url     = {https://doi.org/10.1038/s41598-024-51985-w}
}

@article{muller2019-30837580,
  author  = {Müller, S. and Herde, L. and Preische, O. and Zeller, A. and Heymann, P. and Robens, S. and Elbing, U. and Laske, C.},
  title   = {{Diagnostic value of digital clock drawing test in comparison with CERAD neuropsychological battery total score for discrimination of patients in the early course of Alzheimer's disease from healthy individuals}},
  journal = {Scientific reports},
  year    = {2019},
  doi     = {10.1038/s41598-019-40010-0},
  pmid    = {30837580},
  url     = {https://doi.org/10.1038/s41598-019-40010-0}
}

@article{chen2020-33257744,
  author  = {Chen, S. and Stromer, D. and Alabdalrahim, H. A. and Schwab, S. and Weih, M. and Maier, A.},
  title   = {{Automatic dementia screening and scoring by applying deep learning on clock-drawing tests}},
  journal = {Scientific reports},
  year    = {2020},
  doi     = {10.1038/s41598-020-74710-9},
  pmid    = {33257744},
  url     = {https://doi.org/10.1038/s41598-020-74710-9}
}

@article{tian2021-33420208,
  author  = {Tian, J. and Smith, G. and Guo, H. and Liu, B. and Pan, Z. and Wang, Z. and Xiong, S. and Fang, R.},
  title   = {{Modular machine learning for Alzheimer's disease classification from retinal vasculature}},
  journal = {Scientific reports},
  year    = {2021},
  doi     = {10.1038/s41598-020-80312-2},
  pmid    = {33420208},
  url     = {https://doi.org/10.1038/s41598-020-80312-2}
}

@article{alamro2023-36973386,
  author  = {Alamro, H. and Thafar, M. A. and Albaradei, S. and Gojobori, T. and Essack, M. and Gao, X.},
  title   = {{Exploiting machine learning models to identify novel Alzheimer's disease biomarkers and potential targets}},
  journal = {Scientific reports},
  year    = {2023},
  doi     = {10.1038/s41598-023-30904-5},
  pmid    = {36973386},
  url     = {https://doi.org/10.1038/s41598-023-30904-5}
}

@article{varatharajah2019-30783207,
  author  = {Varatharajah, Y. and Ramanan, V. K. and Iyer, R. and Vemuri, P. and {Alzheimer’s Disease Neuroimaging Initiative}},
  title   = {{Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics}},
  journal = {Scientific reports},
  year    = {2019},
  doi     = {10.1038/s41598-019-38793-3},
  pmid    = {30783207},
  url     = {https://doi.org/10.1038/s41598-019-38793-3}
}

@article{choi2025-40594040,
  author  = {Choi, Dong Hyeok and Ahn, So Hyun and Chung, Yujin and Kim, Jin Sung and Jeong, Jee Hyang and Yoon, Hai‐Jeon},
  title   = {{Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase 18F-Florbetaben PET and clinical features}},
  journal = {Scientific Reports},
  year    = {2025},
  doi     = {10.1038/s41598-025-00743-7},
  pmid    = {40594040},
  url     = {https://doi.org/10.1038/s41598-025-00743-7}
}

@article{richter2025-39994339,
  author  = {Richter, M. and Sobotnicka, Ewelina and Bednorz, Adam},
  title   = {{Cognitive performance classification of older patients using machine learning and electronic medical records}},
  journal = {Scientific Reports},
  year    = {2025},
  doi     = {10.1038/s41598-025-90460-y},
  pmid    = {39994339},
  url     = {https://doi.org/10.1038/s41598-025-90460-y}
}

@article{lu2018-29632364,
  author  = {Lu, D. and Popuri, K. and Ding, G. W. and Balachandar, R. and Beg, M. F. and {Alzheimer’s Disease Neuroimaging Initiative}},
  title   = {{Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images}},
  journal = {Scientific reports},
  year    = {2018},
  doi     = {10.1038/s41598-018-22871-z},
  pmid    = {29632364},
  url     = {https://doi.org/10.1038/s41598-018-22871-z}
}

@article{welberry2020-32472058,
  author  = {Welberry, H. J. and Brodaty, H. and Hsu, B. and Barbieri, S. and Jorm, L. R.},
  title   = {{Measuring dementia incidence within a cohort of 267,153 older Australians using routinely collected linked administrative data}},
  journal = {Scientific reports},
  year    = {2020},
  doi     = {10.1038/s41598-020-65273-w},
  pmid    = {32472058},
  url     = {https://doi.org/10.1038/s41598-020-65273-w}
}

@article{katako2018-30185806,
  author  = {Katako, A. and Shelton, P. and Goertzen, A. L. and Levin, D. and Bybel, B. and Aljuaid, M. and Yoon, H. J. and Kang, D. Y. and others},
  title   = {{Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia}},
  journal = {Scientific reports},
  year    = {2018},
  doi     = {10.1038/s41598-018-31653-6},
  pmid    = {30185806},
  url     = {https://doi.org/10.1038/s41598-018-31653-6}
}

@article{medani2025-40360623,
  author  = {Medani, Mohamed and Elhessewi, Ghada Moh. Samir and Alqahtani, Mohammed Abdulrahman and ASKLANY, SOMIA A. and Alamro, Sulaiman and Albalawneh, Da’ad and Alshammeri, Menwa and Assiri, Mohammed Abdullah},
  title   = {{Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems}},
  journal = {Scientific Reports},
  year    = {2025},
  doi     = {10.1038/s41598-025-97102-3},
  pmid    = {40360623},
  url     = {https://doi.org/10.1038/s41598-025-97102-3}
}

@article{feng2025-39987324,
  author  = {Feng, Gangyi and Zhong, Manli and Huang, Hudie and Zhao, Pu and Zhang, Xiaoyu and Wang, Tao and Gao, Huiling and Xu, He},
  title   = {{Identification of UBE2N as a biomarker of Alzheimer’s disease by combining WGCNA with machine learning algorithms}},
  journal = {Scientific Reports},
  year    = {2025},
  doi     = {10.1038/s41598-025-90578-z},
  pmid    = {39987324},
  url     = {https://doi.org/10.1038/s41598-025-90578-z}
}

@article{venugopalan2021-33547343,
  author  = {Venugopalan, J. and Tong, L. and Hassanzadeh, H. R. and Wang, M. D.},
  title   = {{Multimodal deep learning models for early detection of Alzheimer's disease stage}},
  journal = {Scientific reports},
  year    = {2021},
  doi     = {10.1038/s41598-020-74399-w},
  pmid    = {33547343},
  url     = {https://doi.org/10.1038/s41598-020-74399-w}
}

@article{ali2025-40670451,
  author  = {Ali, Zainab Hassan and Hassan, Esraa and Elgamal, Shimaa and El-Rashidy, Nora Mahmoud},
  title   = {{Developing an explainable machine learning and fog computing-based visual rating scale for the prediction of dementia progression}},
  journal = {Scientific Reports},
  year    = {2025},
  doi     = {10.1038/s41598-025-06310-4},
  pmid    = {40670451},
  url     = {https://doi.org/10.1038/s41598-025-06310-4}
}

@article{kang2025-40715350,
  author  = {Kang, Sung Woo and Lee, Yunjin and Kim, Nayoung and Ok, Sang-Houn and Kim, Pilsu and Park, Ok-Hyun and Kim, Da-Mi and Jang, Yongwoo and others},
  title   = {{Beneficial effect of artificial intelligence care call on memory and depression in community dwelling individuals with dementia}},
  journal = {Scientific Reports},
  year    = {2025},
  doi     = {10.1038/s41598-025-12895-7},
  pmid    = {40715350},
  url     = {https://doi.org/10.1038/s41598-025-12895-7}
}