## 2 Related Work
### Ethical, Legal, and Regulatory Considerations in AI for NDDs  
The responsible development of AI-based healthcare systems--particularly those intended for use in sensitive contexts such as neurodegenerative disease monitoring--requires strict adherence to legal and ethical principles throughout the entire system lifecycle. Foundational values such as fairness, transparency, prevention of harm, and respect for human autonomy have been established at the European level by the High-Level Expert Group on AI (AI HLEG) as core requirements for trustworthy AI [43]. Complementing these principles, UNESCO's Recommendations on the Ethics of Artificial Intelligence emphasize the need for human dignity and safety in the design and deployment of AI technologies [44]. Binding legal frameworks serve to reinforce these ethical foundations. Strict guidelines for handling sensitive health and personal data are established by the GDPR, which requires strong data security, openness, and explicit consent [45]. The National Authority for the Supervision of Personal Data Processing (ANSPDCP), the appropriate public body in charge of guaranteeing the preservation of people's fundamental rights to privacy and personal data, made the GDPR mandatory in Romania in 2018 [46]. The legal framework for medical devices, including software-based instruments used for therapeutic or diagnostic purposes, is updated by the MDR, Regulation (EU) 2017/745. It highlights safety, clinical evaluation, and traceability while introducing the Unique Device Identification (UDI) system [47]. Additionally, the European AI Act establishes a risk-based categorization of AI systems into four levels: unacceptable risk (prohibited), high-risk (e.g., healthcare applications), limited or minimal-risk (e.g., video games, spam filters) [48]. There are significant issues with algorithmic transparency, data security, and clinical accountability when using AI systems for neurodegenerative disease monitoring. To address these, adherence to legal and ethical frameworks throughout the entire system lifecycle is necessary. Romania's National AI Strategy was developed by the Interinstitutional Commission and the Romanian Committee for Artificial Intelligence, which were established by Order No. 20484 (April 2023) [49; 50]. These efforts support the governance framework that guides the development of platforms such as NeuroPredict. Adherence to ethical principles, medical regulations, and data protection laws is necessary for the responsible use of AI in the treatment of neurodegenerative diseases. Informed consent, data minimization, and patient privacy are all guaranteed by GDPR, which is particularly fundamental in situations involving long-term monitoring [51]. Concerns like algorithmic bias, lack of explainability, and opaque decision-making highlight the necessity for strong clinical validation and supervision as AI systems are used in neurology and mental health [52]. To guarantee clinical validity, [PERSON] and [PERSON] [53] emphasize the necessity of precise regulatory standards. In PD and AD, tools like gait monitoring and predictive algorithms must adhere to MDR and respect safety and equity principles. The need for close supervision is further demonstrated by emerging diagnostics such as brain-aging biomarker analysis [54]. The regulatory challenges at the nexus of the AI Act and MDR are demonstrated by the NeuroPredict platform. Given its integration of wearable biosensors and AI-driven analytics for health condition monitoring, the NeuroPredict platform would likely fall under Class IIa or IIb of the MDR, as it performs functions with diagnostic and monitoring intent. This classification implies the need for formal clinical validation and conformity assessment by a notified body. Simultaneously, under the European AI Act, it would be categorized as a high-risk AI system due to its healthcare application, thus subject to requirements for transparency, human oversight, lifecycle risk management, and the implementation of an AI-specific quality management system.