https://dspace.ffh.bg.ac.rs/handle/123456789/3 2026-04-15T11:26:26Z https://dspace.ffh.bg.ac.rs/handle/123456789/2679 Title: The Future of Headache Disorders through AI Tools Authors: Martelletti, Paolo; Petrušić, Igor Editors: Martelletti, Paolo; Leonardi, Matilde; Wijeratne, Tissa Abstract: Artificial intelligence (AI) is rapidly transforming the landscape of headache management by enhancing diagnostic accuracy, optimizing treatment pathways, and supporting global health equity. This chapter reviews the integration of AI tools in the diagnosis and management of headache disorders, with a particular focus on migraine, cluster headache, and post-traumatic headache. Advances in machine learning (ML) and deep learning models applied to clinical data, neuroimaging, and patient-reported outcomes enable more precise migraine subtyping, biomarker discovery, and individualized treatment approaches. AI-based tools, including digital phenotyping and large language models, facilitate symptom tracking, patient education, and decision support in clinical practice. Moreover, emerging applications such as digital twins and biofeedback–virtual reality therapeutics illustrate the potential for highly personalized and preventive care. The chapter also highlights the role of AI in advancing Sustainable Development Goal 3 (SDG3) by reducing disparities in headache care, strengthening health systems, and supporting equitable access to innovations. Overall, AI is poised to revolutionize headache research and clinical practice, aligning technological progress with global public health goals. 2026-02-07T00:00:00Z https://dspace.ffh.bg.ac.rs/handle/123456789/2634 Title: Harnessing Molecularly Imprinted Polymers as Artificial Antibodies in Electrochemical Sensors for Disease Detection and Monitoring Authors: Tasić, Tamara; Milanković, Vedran; Pašti, Igor; Lazarević-Pašti, Tamara Abstract: This chapter explores the integration of Molecularly Imprinted Polymers (MIPs) into electrochemical sensors, focusing on their applications as artificial antibodies in disease detection and monitoring. After discussing the basic principles of electrochemical sensors, we delve into the versatility of MIPs, which allow for the selective recognition of disease-related molecules. Their stability, cost-effectiveness, and non-immunogenicity make them ideal candidates for use in diagnostic technologies. The chapter showcases the synergy between MIPs and electrochemical transduction, converting target-binding events into measurable electrical signals. We highlight case studies where MIP-based electrochemical sensors have demonstrated enhanced sensitivity and specificity in detecting cancer biomarkers, autoimmune disease markers, and infectious agents. These examples underscore the potential of MIP-based sensors in revolutionizing disease management. The discussion covers challenges and future perspectives in the field, addressing the optimization of sensor performance and achieving the desired level of specificity. Additionally, we explore the potential of MIP-based electrochemical sensors as theranostic tools, combining diagnostics with targeted drug delivery and offering a glimpse into personalized medicine. In conclusion, MIP-based electrochemical sensors present a promising frontier in disease detection and monitoring, showcasing the innovative application of artificial antibodies. As technology advances, these biosensing platforms hold great potential to transform healthcare, enabling precise and accessible diagnostics for improved patient outcomes. 2024-01-01T00:00:00Z https://dspace.ffh.bg.ac.rs/handle/123456789/2497 Title: Future Directions in Neuroimaging of Headache Disorders Authors: Petrušić, Igor 2025-03-30T00:00:00Z https://dspace.ffh.bg.ac.rs/handle/123456789/2496 Title: Neuroimaging Studies of Migraine with Aura Authors: Petrušić, Igor; Hadjikhani, Nouchine 2025-03-30T00:00:00Z