Guest Editorial on the Special Issue on Integrating Informatics and Technology for Precision Medicine
Open accessAbstract
The seven papers in this special section examine the latest advances in the field of integrated precision medicine technologies. In the majority of medical conditions common therapeutic approaches are usually effective in only a small percentage of the patient population. Recent scientific discoveries implicate as possible causes of this lack of effect the multifactorial nature of most diseases and the patient variability in disease expression, genetic disposition, and environmental exposures. It has become apparent that in order to improve the response to therapy and long term prognosis, treatment must be specifically tailored to the disease and the patient. Precision medicine is an attempt to maximize effectiveness by taking into account individual variability in clinical presentation, medical history, genes, environment, and lifestyle. It is a leap beyond the promise of “personalization” empowered by recent technological advances. However, progress in precision medicine has been slow due to the lack of “precision” in the traditional research, translation, and clinical practice. Current approaches are largely empirical, fragmented, lack integration, and rely on population statistics, with inadequate feedback between disciplines. In addition, most of the information required for personalization is either missing or unutilized. New technological developments can help overcome these hurdles of imprecision to achieve the full promise of precision medicine.
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Precision medicine is an emerging approach for administering healthcare that aims to improve the accuracy with which clinical decisions are rendered towards improving the delivery of personalized treatment and therapy planning for patients.
“Precision medicine is an emerging approach for administering healthcare that aims to improve the accuracy with which clinical decisions are rendered towards improving the delivery of personalized treatment and therapy planning for patients as depicted in Fig. 3 [67].”
From AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020) · cites this paper as [67]
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AI in Medical Imaging Informatics: Current Challenges and Future Directions
Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2991043 · Cited by 713 · see citing works
“3 [67].”
Self-citationDitton, E., Johnson, S. J., Hodyl, N. A., Flynn, T. S., Pollack, M. R. P., Ribbons, K., Walker, F. R., & Nilsson, M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01061 · Cited by 68 · see citing works
“This is particularly the case since many of these factors fall outside of the usual purview of surgeons and rehabilitation providers (Negrini, 2019; Pattichis et al., 2019).”
BackgroundMethodArtificial Intelligence in Cosmetic Dermatology: A Systematic Literature Review
Vatiwutipong, P., Vachmanus, S., Noraset, T., & Tuarob, S. (2023) · IEEE Access · doi:10.1109/access.2023.3295001 · Cited by 67 · see citing works
“To accomplish this, the development of intelligent technologies is needed to overcome these challenges and fulfill this goal [121].”
BackgroundLiu, J., Ji, J., Jia, X., & Zhang, A. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2946676 · Cited by 25 · see citing works
A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations
Liu, X., Chen, C.-H., Karvela, M., & Toumazou, C. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2978667 · Cited by 21 · see citing works
“Throughout the past decades, health care treatment was shifting from a disease-centred model towards a patient-centred model, and mostly using a genetic approach or a wearable monitoring device [14], [15].”
BackgroundBinas, D. A., Tzanakakis, P., Economopoulos, T. L., Konidari, M., Bourgioti, C. I., Moulopoulos, L. A., & Matsopoulos, G. K. (2023) · Cancers · doi:10.3390/cancers15041058 · Cited by 17 · see citing works
2019 Index IEEE Journal of Biomedical and Health Informatics Vol. 23
(2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2966416
- Authors
- Pattichis, C. S., Pitris, C., Liang, J., & Zhang, Y.
- Affiliations
- University of Cyprus (CY)
- University of Illinois Urbana-Champaign (US)
- Venue
- IEEE Journal of Biomedical and Health Informatics
- Published
- 2019-01
- Volume
- 23
- Issue
- 1
- Pages
- 12-13
- ISSN
- 2168-2194 (ISSN-L)
- 2168-2208
- OpenAlex
- W2910577213
- Cited by
- 7
- References
- 0
- Citations by year
- 2023: 2 · 2020: 3 · 2019: 2
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- IEEE Journal of Biomedical and Health Informatics (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- precision medicine, personalized medicine, patient heterogeneity, genetic susceptibility, environmental exposure, clinical practice integration, health informatics
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