Cristina-Gabriela Gheorghe

Dr. Cristina-Gabriela Gheorghe

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 July 2025 in Future Internet
Verified
Journal Article
Open access
PDF file
MIMarilena Ianculescu
Marilena Ianculescu
LBLidia Bajenaru
Lidia Bajenaru
AVAna Vasilevschi
Ana Vasilevschi
MGMaria Gheorghe-Moisii
Maria Gheorghe-Moisii
CGCristina-Gabriela Gheorghe
Cristina-Gabriela Gheorghe
On a worldwide scale, neurodegenerative diseases, including multiple sclerosis, Parkinson’s, and Alzheimer’s, face considerable healthcare challenges demanding the development of novel approaches to early detection and efficient treatment. With its ability to provide real-time patient monitoring, customized medical care, and advanced predictive analytics, artificial intelligence (AI) is fundamentally transforming the way healthcare is provided. Through the integration of wearable physiological sensors, motion sensors, and neurological assessment tools, the NeuroPredict platform harnesses AI and smart sensor technologies to enhance the management of specific neurodegenerative diseases. Machine learning algorithms process these data flows to find patterns that point out disease evolution. This paper covers the design and architecture of the NeuroPredict platform, stressing the ethical and regulatory requirements that guide its development. Initial development of AI algorithms for disease monitoring, technical achievements, and constant enhancements driven by early user feedback are addressed in the discussion section. To ascertain the platform’s trustworthiness and data security, it also points towards risk analysis and mitigation approaches. The NeuroPredict platform’s capability for achieving AI-driven smart healthcare solutions is highlighted, even though it is currently in the development stage. Subsequent research is expected to focus on boosting data integration, expanding AI models, and providing regulatory compliance for clinical application. The current results are based on incremental laboratory tests using simulated user roles, with no clinical patient data involved so far. This study reports an experimental technology evaluation of modular components of the NeuroPredict platform, integrating multimodal sensors and machine learning pipelines in a laboratory-based setting, with future co-design and clinical validation foreseen for a later project phase.

29 March 2024 in Revista Română de Informatică şi Automatică
Verified
Journal Article
Open access
MGMaria Gheorghe-Moisii
Maria Gheorghe-Moisii
CGCristina-Gabriela Gheorghe
Cristina-Gabriela Gheorghe
SSSorin Soviany
Sorin Soviany

29 November 2023 in Romanian Cyber Security Journal
Verified
Journal Article
Open access
SSSorin Soviany
Sorin Soviany
CGCristina-Gabriela Gheorghe
Cristina-Gabriela Gheorghe
ROCYS is a knowledge resource for practitioners, scientists, and researchers working in various fields of cyber security, hacking, digital forensics, cyber warfare, viruses and worms domain or critical infrastructure protection area.

4 December 2024 in Romanian Cyber Security Journal
Verified
Journal Article
Closed access
SSSorin Soviany
Sorin Soviany
CGCristina-Gabriela Gheorghe
Cristina-Gabriela Gheorghe
MGMaria Gheorghe-Moisii
Maria Gheorghe-Moisii
ROCYS is a knowledge resource for practitioners, scientists, and researchers working in various fields of cyber security, hacking, digital forensics, cyber warfare, viruses and worms domain or critical infrastructure protection area.

3 November 2022 in Romanian Cyber Security Journal
Verified
Journal Article
Closed access
ADAndreea Dinu
Andreea Dinu
CGCristina-Gabriela Gheorghe
Cristina-Gabriela Gheorghe
CGCristian Gruia
Cristian Gruia
ROCYS is a knowledge resource for practitioners, scientists, and researchers working in various fields of cyber security, hacking, digital forensics, cyber warfare, viruses and worms domain or critical infrastructure protection area.