Advances in Artificial Intelligence and Machine Learning for Neurodegenerative Disease: A Literature Review

Yahya Abdul Rehman Shah,Sara Muddassir Qureshi, Hamza Ahmed Qureshi, Saad Ur Rehman Shah, Ahsan Ahmad, Ashish Shiwlani

Artificial intelligence (AI), Neurodegenerative diseases, Alzheimer’s disease, Parkinson’s disease, Data heterogeneity, Personalized medicine, Federated Learning, and Synthetic Data.

The current trajectory of AI and ML in revitalizing our strategies to handle neurodegenerative illnesses is one of a kind. These remarkable technologies do this by allowing prompt diagnosis, customized care, and even new ideas about how we can treat these ailments. Therefore, this review's main objective is to evaluate the use of artificial intelligence (AI) and machine learning (ML) techniques in neurodegenerative disorder management, specifically on their impact on clinical practices and research. Using PRISMA guidelines as a reference point, we performed an extensive literature search across PubMed, IEEE Xplore, Scopus, and Web of Science from 2018 through 2024. Out of 1,050 unique records identified through rigorous screening and full-text review process, only 70 articles were selected for further analysis. The studies varied regarding their goals, the AI/ML techniques they applied, the outcomes they assessed, and the problems they encountered. Our review shows that AI and ML significantly improve the accuracy of diagnosing and treating neurodegenerative diseases, such as Alzheimer's and Parkinson's, particularly in their early stages. AI-based tools have demonstrated superior performance to traditional methods, especially in early diagnosis and predicting treatment responses. Interestingly, the interface between neurobiology and AI defines new avenues to comprehend brain networks and investigate emerging technologies as brain-computer interfaces. Nevertheless, this advancement also delves into questions about ethics and regulation involving algorithmic biases, data set inconsistencies, and privacy issues. Though adopting artificial intelligence (AI) and machine learning (ML) has a lot to contribute to changing the management of neurodegenerative diseases, their successful application depends on continuous interdisciplinary research, stakeholder collaboration, and careful consideration of the ethical challenges involved. Looking into the future, subsequent studies need to emphasize improving AI's understanding, stopping bias, and developing tougher data sets. Another area of great interest is the investigation of AI-held anticipatory models for early findings, which may result in movement from cure to avoidance. The capacity of artificial intelligence to explore massive volumes of information would enable us to identify more cancer markers and customize therapy methods for patients suffering from brain degenerative diseases.Addressing these issues is critical in tapping into the complete potential of these healthcare innovations while broadening our knowledge about neurodegenerative states.

https://doi.org/10.31871/WJRR.19.3.8