[1] AARSLAND D, BATZU L, HALLIDAY G M, et al. Parkinson disease-associated cognitive impairment[J]. Nat Rev Dis Primers, 2021, 7(1): 47. [2] MACLAGAN L C, VISANJI N P, CHENG Y, et al. Identifying drugs with disease-modifying potential in Parkinson’s disease using artificial intelligence and pharmacoepidemiology[J]. Pharmacoepidemiol Drug Saf, 2020, 29(8): 864-872. [3] XU T, DONG W, LIU J, et al. Disease burden of Parkinson’s disease in China and its provinces from 1990 to 2021: findings from the global burden of disease study 2021[J]. Lancet Reg Health West Pac, 2024, 46: 101078. [4] TOLOSA E, GARRIDO A, SCHOLZ S W, et al. Challenges in the diagnosis of Parkinson’s disease[J]. Lancet Neurol, 2021, 20(5): 385-397. [5] ARMSTRONG M J, OKUN M S. Diagnosis and treatment of Parkinson disease: a review[J]. JAMA, 2020, 323(6): 548-560. [6] KWON D K, KWATRA M, WANG J, et al. Levodopa-induced dyskinesia in Parkinson’s disease: pathogenesis and emerging treatment strategies[J]. Cells, 2022, 11(23): 3736. [7] GUTOWSKI T, ANTKIEWICZ R, SZLUFIK S. Machine learning with optimization to create medicine intake schedules for Parkinson’s disease patients[J]. PLoS One, 2023, 18(10): e0293123. [8] WU K M, XU Q H, LIU Y Q, et al. Neuronal FAM171A2 mediates α-synuclein fibril uptake and drives Parkinson’s disease[J]. Science, 2025, 387(6736): 892-900. [9] HARIZ M, BLOMSTEDT P. Deep brain stimulation for Parkinson’s disease[J]. J Intern Med, 2022, 292(5): 764-778. [10] ZHOU T, XU W, SHI W. Investigation of the mechanism of action of deep brain stimulation for the treatment of Parkinson’s disease[J]. Cogn Neurodyn, 2024, 18(2): 581-595. [11] NEUMANN W J, TURNER R S, BLANKERTZ B, et al. Toward electrophysiology-based intelligent adaptive deep brain stimulation for movement disorders[J]. Neurotherapeutics, 2019, 16(1): 105-118. [12] ROEDIGER J, DEMBEK T A, ACHTZEHN J, et al. Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm[J]. Lancet Digit Health, 2023, 5(2): e59-e70. [13] GOETZ C G, TILLEY B C, SHAFTMAN S R, et al. Movement disorder society-sponsored revision of the unified Parkinson’s disease rating scale (MDS-UPDRS): scale presentation and clinimetric testing results[J]. Mov Disord, 2008, 23(15): 2129-2170. [14] YANG Y, YUAN Y, ZHANG G, et al. Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals[J]. Nat Med, 2022, 28(10): 2207-2215. [15] PURRER V, POHL E, LUECKEL J M, et al. Artificial-intelligence-based MRI brain volumetry in patients with essential tremor and tremor-dominant Parkinson’s disease[J]. Brain Commun, 2023, 5(6): fcad271. [16] LI C, HUI D, WU F, et al. Automatic diagnosis of Parkinson’s disease using artificial intelligence base on routine T1-weighted MRI[J]. Front Med, 2024, 10: 1303501. [17] REDDY S, GIRI D, PATEL R. Artificial intelligence diagnosis of Parkinson’s disease from MRI scans[J]. Cureus, 2024, 16(4): e58841. [18] BURTSCHER J, MORAUD E M, MALATESTA D, et al. Exercise and gait/movement analyses in treatment and diagnosis of Parkinson’s disease[J]. Ageing Res Rev, 2024, 93: 102147. [19] ILEŞAN R R, CORDOŞ C G, MIHÄILÄ L I, et al. Proof of concept in artificial-intelligence-based wearable gait monitoring for Parkinson’s disease management optimization[J]. Biosensors, 2022, 12(4): 189. [20] 张立新, 白定群, 白玉龙,等. 下肢康复机器人临床应用专家共识[J]. 康复学报,2023,33(5):383-396. [21] KWON S H, PARK J K, KOH Y H. A systematic review and meta-analysis on the effect of virtual reality-based rehabilitation for people with Parkinson’s disease[J]. J Neuroeng Rehabil, 2023, 20(1): 94. [22] KASHIF M, AHMAD A, BANDPEI M A M, et al. Combined effects of virtual reality techniques and motor imagery on balance, motor function and activities of daily living in patients with Parkinson’s disease: a randomized controlled trial[J]. BMC Geriatr, 2022, 22(1): 381. [23] GULCAN K, GUCLU-GUNDUZ A, YASAR E, et al. The effects of augmented and virtual reality gait training on balance and gait in patients with Parkinson’s disease[J]. Acta Neurol Belg, 2023, 123(5): 1917-1925. [24] SAXON M, TRIPATHI A, JIAO Y, et al. Robust estimation of hypernasality in dysarthria with acoustic model likelihood features[J]. IEEE/ACM Trans Audio Speech Lang Process, 2020, 28: 2511-2522. [25] KUMAR R, TRIPATHY M, KUMAR N, et al. Management of Parkinson’s disease dysarthria: can artificial intelligence provide the solution?[J]. Ann Indian Acad Neurol, 2022, 25(5): 810-816. [26] 韦朝霞,李丽华,罗庆禄,等. 人工智能在帕金森病构音障碍研究中的应用进展[J]. 中华神经科杂志,2024,57(11):1259-1263. [27] AMATO F, BORZÌ L, OLMO G, et al. An algorithm for Parkinson’s disease speech classification based on isolated words analysis[J]. Health Inf Sci Syst, 2021, 9(1): 32. [28] 刘培培, 巫嘉陵. 基于视频信息的帕金森病智能辅助诊断与治疗进展[J]. 中国现代神经疾病杂志, 2023, 23(1): 35-39. [29] KANG M G, YUN S J, SHIN H I, et al. Effects of robot-assisted gait training in patients with Parkinson’s disease: study protocol for a randomized controlled trial[J]. Trials, 2019, 20(1): 15. [30] OMBERG L, CHAIBUB NETO E, PERUMAL T M, et al. Remote smartphone monitoring of Parkinson’s disease and individual response to therapy[J]. Nat Biotechnol, 2022, 40(4): 480-487. [31] XU X, ZENG Z, QI Y, et al. Remote video-based outcome measures of patients with Parkinson’s disease after deep brain stimulation using smartphones: a pilot study[J]. Neurosurg Focus, 2021, 51(5): E2. [32] BOUGEA A, ANGELOPOULOU E. Non-motor disorders in parkinson disease and other parkinsonian syndromes[J]. Medicina, 2024, 60(2): 309. [33] MEINERT E, MILNE-IVES M, CHAUDHURI K R, et al. The impact of a digital artificial intelligence system on the monitoring and self-management of nonmotor symptoms in people with parkinson disease: proposal for a phase 1 implementation study[J]. JMIR Res Protoc, 2022, 11(9): e40317. [34] JANSSEN DAALEN J M, VAN DEN BERGH R, PRINS E M, et al. Digital biomarkers for non-motor symptoms in Parkinson’s disease: the state of the art[J]. NPJ Digit Med, 2024, 7(1): 186. [35] ALTHAM C, ZHANG H, PEREIRA E. Machine learning for the detection and diagnosis of cognitive impairment in Parkinson’s disease: a systematic review[J]. PLoS One, 2024, 19(5): e0303644. [36] WU Y, CHENG Y, XIAO Y, et al. The role of machine learning in cognitive impairment in parkinson disease: systematic review and meta-analysis[J]. J Med Internet Res, 2025, 27: e59649. [37] GODOY C A, MIELE F, MÄKITIE L, et al. Attitudes toward the adoption of remote patient monitoring and artificial intelligence in Parkinson’s disease management: perspectives of patients and neurologists[J]. Patient, 2024, 17(3): 275-285. |