Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2
Abstract Part 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-driven drug discovery. Digital twins, as dy...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | The Journal of Headache and Pain |
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| Online Access: | https://doi.org/10.1186/s10194-024-01944-7 |
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| author | Igor Petrušić Chia-Chun Chiang David Garcia-Azorin Woo-Seok Ha Raffaele Ornello Lanfranco Pellesi Eloisa Rubio-Beltrán Ruth Ruscheweyh Marta Waliszewska-Prosół William Wells-Gatnik |
| author_facet | Igor Petrušić Chia-Chun Chiang David Garcia-Azorin Woo-Seok Ha Raffaele Ornello Lanfranco Pellesi Eloisa Rubio-Beltrán Ruth Ruscheweyh Marta Waliszewska-Prosół William Wells-Gatnik |
| author_sort | Igor Petrušić |
| collection | DOAJ |
| description | Abstract Part 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-driven drug discovery. Digital twins, as dynamic digital representations of patients, offer opportunities for personalized headache management by integrating diverse datasets such as neuroimaging, multiomics, and wearable sensor data to advance headache research, optimize treatment, and enable virtual trials. In addition, AI-driven wearable devices equipped with next-generation biosensors combined with multi-agent chatbots could enable real-time physiological and biochemical monitoring, diagnosing, facilitating early headache attack forecasting and prevention, disease tracking, and personalized interventions. Furthermore, AI-driven advances in drug discovery leverage machine learning and generative AI to accelerate the identification of novel therapeutic targets and optimize treatment strategies for migraine and other headache disorders. Despite these advances, challenges such as data standardization, model explainability, and ethical considerations remain pivotal. Collaborative efforts between clinicians, biomedical and biotechnological engineers, AI scientists, legal representatives and bioethics experts are essential to overcoming these barriers and unlocking AI’s full potential in transforming headache research and healthcare. This is a call to action in proposing novel frameworks for integrating AI-based technologies into headache care. Graphical Abstract |
| format | Article |
| id | doaj-art-a16f11eeccd340799351df8ec49bf6ab |
| institution | Kabale University |
| issn | 1129-2377 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | The Journal of Headache and Pain |
| spelling | doaj-art-a16f11eeccd340799351df8ec49bf6ab2025-01-05T12:41:49ZengBMCThe Journal of Headache and Pain1129-23772025-01-0126111310.1186/s10194-024-01944-7Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2Igor Petrušić0Chia-Chun Chiang1David Garcia-Azorin2Woo-Seok Ha3Raffaele Ornello4Lanfranco Pellesi5Eloisa Rubio-Beltrán6Ruth Ruscheweyh7Marta Waliszewska-Prosół8William Wells-Gatnik9Laboratory for Advanced Analysis of Neuroimages, Faculty of Physical Chemistry, University of BelgradeDepartment of Neurology, Mayo ClinicDepartment of Medicine, Toxicology and Dermatology, Faculty of Medicine, University of ValladolidDepartment of Neurology, Severance Hospital, Yonsei University College of MedicineDepartment of Biotechnological and Applied Clinical Sciences, University of L’AquilaClinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern DenmarkHeadache Group. Wolfson Sensory, Pain and Regeneration Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College LondonDepartment of Neurology, LMU University Hospital, LMU MunichDepartment of Neurology, Wrocław Medical UniversityUnitelma Sapienza University of RomeAbstract Part 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-driven drug discovery. Digital twins, as dynamic digital representations of patients, offer opportunities for personalized headache management by integrating diverse datasets such as neuroimaging, multiomics, and wearable sensor data to advance headache research, optimize treatment, and enable virtual trials. In addition, AI-driven wearable devices equipped with next-generation biosensors combined with multi-agent chatbots could enable real-time physiological and biochemical monitoring, diagnosing, facilitating early headache attack forecasting and prevention, disease tracking, and personalized interventions. Furthermore, AI-driven advances in drug discovery leverage machine learning and generative AI to accelerate the identification of novel therapeutic targets and optimize treatment strategies for migraine and other headache disorders. Despite these advances, challenges such as data standardization, model explainability, and ethical considerations remain pivotal. Collaborative efforts between clinicians, biomedical and biotechnological engineers, AI scientists, legal representatives and bioethics experts are essential to overcoming these barriers and unlocking AI’s full potential in transforming headache research and healthcare. This is a call to action in proposing novel frameworks for integrating AI-based technologies into headache care. Graphical Abstracthttps://doi.org/10.1186/s10194-024-01944-7Digital twinBiosensorsWearable devicesDrug discoveryMigraineMachine learning |
| spellingShingle | Igor Petrušić Chia-Chun Chiang David Garcia-Azorin Woo-Seok Ha Raffaele Ornello Lanfranco Pellesi Eloisa Rubio-Beltrán Ruth Ruscheweyh Marta Waliszewska-Prosół William Wells-Gatnik Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 The Journal of Headache and Pain Digital twin Biosensors Wearable devices Drug discovery Migraine Machine learning |
| title | Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 |
| title_full | Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 |
| title_fullStr | Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 |
| title_full_unstemmed | Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 |
| title_short | Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 |
| title_sort | influence of next generation artificial intelligence on headache research diagnosis and treatment the junior editorial board members vision part 2 |
| topic | Digital twin Biosensors Wearable devices Drug discovery Migraine Machine learning |
| url | https://doi.org/10.1186/s10194-024-01944-7 |
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