Version 1
: Received: 12 October 2024 / Approved: 14 October 2024 / Online: 14 October 2024 (15:39:48 CEST)
How to cite:
Olawade, D. B.; Teke, J.; Adeleye, K. K.; Egbon, E.; Weerasinghe, K.; Ovsepian, S.; Boussios, S. Artificial Intelligence – Guided Cancer Therapy for Patients with Migraine Comorbidities. Preprints2024, 2024101091. https://doi.org/10.20944/preprints202410.1091.v1
Olawade, D. B.; Teke, J.; Adeleye, K. K.; Egbon, E.; Weerasinghe, K.; Ovsepian, S.; Boussios, S. Artificial Intelligence – Guided Cancer Therapy for Patients with Migraine Comorbidities. Preprints 2024, 2024101091. https://doi.org/10.20944/preprints202410.1091.v1
Olawade, D. B.; Teke, J.; Adeleye, K. K.; Egbon, E.; Weerasinghe, K.; Ovsepian, S.; Boussios, S. Artificial Intelligence – Guided Cancer Therapy for Patients with Migraine Comorbidities. Preprints2024, 2024101091. https://doi.org/10.20944/preprints202410.1091.v1
APA Style
Olawade, D. B., Teke, J., Adeleye, K. K., Egbon, E., Weerasinghe, K., Ovsepian, S., & Boussios, S. (2024). Artificial Intelligence – Guided Cancer Therapy for Patients with Migraine Comorbidities. Preprints. https://doi.org/10.20944/preprints202410.1091.v1
Chicago/Turabian Style
Olawade, D. B., Saak Ovsepian and Stergios Boussios. 2024 "Artificial Intelligence – Guided Cancer Therapy for Patients with Migraine Comorbidities" Preprints. https://doi.org/10.20944/preprints202410.1091.v1
Abstract
Background: Cancer remains a leading cause of death worldwide. The progress in effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy.
Objective: This narrative review explores the role of AI in refining anticancer therapy through personalized profiling, with a specific focus on cancer patients with co-morbid migraine.
Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Google Scholar. Studies were selected based on their relevance to AI applications in oncology and migraine management, with a focus on personalized medicine and predictive modeling. Key themes were synthesized to provide an overview of recent developments, challenges, and emerging directions.
Results: AI technologies such as machine learning (ML), deep learning (DL), and natural language processing (NLP) have become instrumental in discovery of genetic and molecular biomarkers to cancer and migraine. These technologies also enable predictive analytics for assessing the impact of migraine on cancer therapy in co-morbid cases, predicting outcomes and provide clinical decision support systems (CDSS) for real-time treatment adjustments.
Conclusion: AI holds significant potential to improve the precision and effectiveness of cancer management and therapy, particularly for cancer patients with co-morbid migraine. Nevertheless, challenges remain over data integration, clinical validation, and ethical consideration, which must be addressed to appreciate the full potential for outlines approach.
Public Health and Healthcare, Health Policy and Services
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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