The Use of Artificial Intelligence in the Management of Neurodegenerative Disorders; Focus on Alzheimer's Disease
Artificial Intelligence and Alzheimer’s Disease
DOI:
https://doi.org/10.31661/gmj.v12i.3061Keywords:
Artificial Intelligence, Neurodegenerative Diseases, AlzheimerAbstract
Recent advances in artificial intelligence (AI) have shown great promise in the diagnosis, prediction, treatment plans, and monitoring the progression of neurodegenerative disorders. AI algorithms can analyze large amounts of data from various sources, including medical images, quantifiable proteins in urine, blood, and cerebrospinal fluid (CSF), genetic information, clinical records, Electroencephalography (EEG) signals, driving behaviors, etc. Alzheimer's disease as one of the most common neurodegenerative disorders. This study specifically explores the possible application of AI in the diagnosis, prediction, monitoring of disease progression, classifying, finding new biomarkers and drugs, and personalizing treatment plans of AD.
References
Hasani N, Morris MA, Rahmim A, Summers RM, Jones E, Siegel E et al. Trustworthy artificial intelligence in medical imaging. PET clinics. 2022;17(1):1-12. https://doi.org/10.1016/j.cpet.2021.09.007https://doi.org/10.1016/j.cpet.2021.09.006 Malik P, Pathania M, Rathaur VK. Overview of artificial intelligence in medicine. Fam Med Prim. 2019;8(7):2328. https://doi.org/10.4103/jfmpc.jfmpc_440_19PMid:31463251 PMCid:PMC6691444 Karimi A, HaddadPajouh H. Artificial intelligence, important assistant of scientists and physicians. Galen Medical Journal. 2020;9:e2048-e. https://doi.org/10.31661/gmj.v9i0.2048PMid:34466625 PMCid:PMC8343766 Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc. 2020;92(4):807-12. https://doi.org/10.1016/j.gie.2020.06.040PMid:32565184 Briganti G, Le Moine O. Artificial intelligence in medicine: today and tomorrow. Front Med. 2020;7:27. https://doi.org/10.3389/fmed.2020.00027PMid:32118012 PMCid:PMC7012990 Hansson O. Biomarkers for neurodegenerative diseases. Nat Med. 2021;27(6):954-63. https://doi.org/10.1038/s41591-021-01382-xPMid:34083813 Wilson DM, Cookson MR, Van Den Bosch L, Zetterberg H, Holtzman DM, Dewachter I. Hallmarks of neurodegenerative diseases. Cell. 2023;186(4):693-714. https://doi.org/10.1016/j.cell.2022.12.032PMid:36803602 Dugger BN, Dickson DW. Pathology of neurodegenerative diseases. Cold Spring Harb. 2017;9(7):a028035. https://doi.org/10.1101/cshperspect.a028035PMid:28062563 PMCid:PMC5495060 Terreros-Roncal J, Moreno-Jiménez E, Flor-García M, Rodríguez-Moreno C, Trinchero MF, Cafini F et al. Impact of neurodegenerative diseases on human adult hippocampal neurogenesis. Science. 2021;374(6571):1106-13. https://doi.org/10.1126/science.abl5163PMid:34672693 PMCid:PMC7613437 Scheltens P, De Strooper B, Kivipelto M, Holstege H, Chételat G, Teunissen CE et al. Alzheimer's disease. Lancet. 2021;397(10284):1577-90. https://doi.org/10.1016/S0140-6736(20)32205-4PMid:33667416 Srivastava S, Ahmad R, Khare SK. Alzheimer's disease and its treatment by different approaches: A review. Eur J Med Chem. 2021;216:113320. https://doi.org/10.1016/j.ejmech.2021.113320PMid:33652356 Dubois B, Villain N, Frisoni GB, Rabinovici GD, Sabbagh M, Cappa S et al. Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group. Lancet Neurol. 2021;20(6):484-96. https://doi.org/10.1016/S1474-4422(21)00066-1PMid:33933186 El-Sappagh S, Alonso JM, Islam S, Sultan AM, Kwak KS. A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease. Sci Rep. 2021;11(1):1-26. https://doi.org/10.1038/s41598-021-82098-3PMid:33514817 PMCid:PMC7846613 Tăuţan A-M, Ionescu B, Santarnecchi E. Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques. Artif Intell Med. 2021;117:102081. https://doi.org/10.1016/j.artmed.2021.102081PMid:34127244 Myszczynska MA, Ojamies PN, Lacoste AM, Neil D, Saffari A, Mead R et al. Applications of machine learning to diagnosis and treatment of neurodegenerative diseases. Nat Rev Neurol. 2020;16(8):440-56. https://doi.org/10.1038/s41582-020-0377-8PMid:32669685 Fabrizio C, Termine A, Caltagirone C, Sancesario G. Artificial intelligence for Alzheimer's disease: promise or challenge? Diagnostics. 2021;11(8):1473. https://doi.org/10.3390/diagnostics11081473PMid:34441407 PMCid:PMC8391160 Tang X. The role of artificial intelligence in medical imaging research. BJR| Open. 2019;2(1):20190031. https://doi.org/10.1259/bjro.20190031 Fazal MI, Patel ME, Tye J, Gupta Y. The past, present and future role of artificial intelligence in imaging. Eur J Radiol. 2018;105:246-50. https://doi.org/10.1016/j.ejrad.2018.06.020PMid:30017288 Chang C-H, Lin C-H, Lane H-Y. Machine learning and novel biomarkers for the diagnosis of Alzheimer's disease. Int J Mol Sci. 2021;22(5):2761. https://doi.org/10.3390/ijms22052761PMid:33803217 PMCid:PMC7963160 Ryzhikova E, Ralbovsky NM, Sikirzhytski V, Kazakov O, Halamkova L, Quinn J et al. Raman spectroscopy and machine learning for biomedical applications: Alzheimer's disease diagnosis based on the analysis of cerebrospinal fluid. Spectrochim Acta A Mol Biomol. 2021;248:119188. https://doi.org/10.1016/j.saa.2020.119188PMid:33268033 Ficiarà E, Boschi S, Ansari S, D'Agata F, Abollino O, Caroppo P et al. Machine Learning Profiling of Alzheimer's Disease Patients Based on Current Cerebrospinal Fluid Markers and Iron Content in Biofluids. Front Aging Neurosci. 2021;13:607858. https://doi.org/10.3389/fnagi.2021.607858PMid:33692679 PMCid:PMC7937894 de la Fuente Garcia S, Ritchie CW, Luz S. Artificial intelligence, speech, and language processing approaches to monitoring Alzheimer's disease: a systematic review. J Alzheimer's Dis. 2020;78(4):1547-74. https://doi.org/10.3233/JAD-200888PMid:33185605 PMCid:PMC7836050 König A, Satt A, Sorin A, Hoory R, Toledo-Ronen O, Derreumaux A et al. Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease. Alzheimers Dement. 2015;1(1):112-24. https://doi.org/10.1016/j.dadm.2014.11.012PMid:27239498 PMCid:PMC4876915 Fristed E, Skirrow C, Meszaros M, Lenain R, Meepegama U, Papp KV et al. Leveraging speech and artificial intelligence to screen for early Alzheimer's disease and amyloid beta positivity. Brain Commun. 2022;4(5):fcac231. https://doi.org/10.1093/braincomms/fcac231PMid:36381988 PMCid:PMC9639797 Rasmussen J, Langerman H. Alzheimer's disease-why we need early diagnosis. Degener Neurol Neuromuscul Dis. 2019:123-30. https://doi.org/10.2147/DNND.S228939PMid:31920420 PMCid:PMC6935598 Liu X, Chen K, Wu T, Weidman D, Lure F, Li J. Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease. Transl Res. 2018;194:56-67. https://doi.org/10.1016/j.trsl.2018.01.001PMid:29352978 PMCid:PMC5875456 Chen H, Li W, Sheng X, Ye Q, Zhao H, Xu Y et al. Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer's disease: a preliminary study. Eur Radiol. 2022;32:448-59. https://doi.org/10.1007/s00330-021-08080-9PMid:34109489 Wolz R, Julkunen V, Koikkalainen J, Niskanen E, Zhang DP, Rueckert D et al. Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease. PLoS One. 2011;6(10):e25446. https://doi.org/10.1371/journal.pone.0025446PMid:22022397 PMCid:PMC3192759 Zhang T, Liao Q, Zhang D, Zhang C, Yan J, Ngetich R et al. Predicting MCI to AD conversation using integrated sMRI and rs-fMRI: machine learning and graph theory approach. Front Aging Neurosci. 2021;13:688926. https://doi.org/10.3389/fnagi.2021.688926PMid:34421570 PMCid:PMC8375594 Zhao X, Ang CKE, Acharya UR, Cheong KH. Application of Artificial Intelligence techniques for the detection of Alzheimer's disease using structural MRI images. Biocybern Biomed Eng. 2021;41(2):456-73. https://doi.org/10.1016/j.bbe.2021.02.006 Eskildsen SF, Coupé P, García-Lorenzo D, Fonov V, Pruessner JC, Collins DL et al. Prediction of Alzheimer's disease in subjects with mild cognitive impairment from the ADNI cohort using patterns of cortical thinning. Neuroimage. 2013;65:511-21. https://doi.org/10.1016/j.neuroimage.2012.09.058PMid:23036450 PMCid:PMC4237400 Ghosh R, Cingreddy AR, Melapu V, Joginipelli S, Kar S. Application of artificial intelligence and machine learning techniques in classifying extent of dementia across alzheimer's image data. IJQSPR. 2021;6(2):29-46. https://doi.org/10.4018/IJQSPR.2021040103 Challis E, Hurley P, Serra L, Bozzali M, Oliver S, Cercignani M. Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI. Neuroimage. 2015;112:232-43. https://doi.org/10.1016/j.neuroimage.2015.02.037PMid:25731993 Li Q, Wu X, Xu L, Chen K, Yao L, Initiative AsDN. Classification of Alzheimer's disease, mild cognitive impairment, and cognitively unimpaired individuals using multi-feature kernel discriminant dictionary learning. Front Comput Neurosci. 2018;11:117. https://doi.org/10.3389/fncom.2017.00117PMid:29375356 PMCid:PMC5767247 German DC, Gurnani P, Nandi A, Garner HR, Fisher W, Diaz-Arrastia R et al. Serum biomarkers for Alzheimer's disease: proteomic discovery. Biomed Pharmacother. 2007;61(7):383-9. https://doi.org/10.1016/j.biopha.2007.05.009PMid:17614251 Yilmaz A, Ustun I, Ugur Z, Akyol S, Hu WT, Fiandaca MS et al. A Community-based study identifying metabolic biomarkers of mild cognitive impairment and Alzheimer's disease using artificial intelligence and machine learning. J Alzheimer's Dis. 2020;78(4):1381-92. https://doi.org/10.3233/JAD-200305PMid:33164929 Yilmaz A, Ugur Z, Bisgin H, Akyol S, Bahado-Singh R, Wilson G et al. Targeted metabolic profiling of urine highlights a potential biomarker panel for the diagnosis of Alzheimer's disease and mild cognitive impairment: a pilot study. Metabolites. 2020;10(9):357. https://doi.org/10.3390/metabo10090357PMid:32878308 PMCid:PMC7569858 Salvatore C, Cerasa A, Battista P, Gilardi MC, Quattrone A, Castiglioni I et al. Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach. Front Neurosci. 2015;9:307. https://doi.org/10.3389/fnins.2015.00307PMid:26388719 PMCid:PMC4555016 Ai R, Jin X, Tang B, Yang G, Niu Z, Fang EF. Ageing and alzheimer's disease: Application of artificial intelligence in mechanistic studies, diagnosis, and drug development. Artif Intell Med Springer. 2021; p: 1-16. https://doi.org/10.1007/978-3-030-58080-3_74-1 Vatansever S, Schlessinger A, Wacker D, Kaniskan HÜ, Jin J, Zhou MM et al. Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions. Med Res Rev. 2021;41(3):1427-73. https://doi.org/10.1002/med.21764PMid:33295676 PMCid:PMC8043990 Farooq A, Anwar S, Awais M, Alnowami M. Artificial intelligence based smart diagnosis of Alzheimer's disease and mild cognitive impairment. In2017 International Smart cities conference (ISC2) 2017 Sep 14 (pp. 1-4). IEEE. https://doi.org/10.1109/ISC2.2017.8090871PMid:29445430 PMCid:PMC5805895
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