TY - CHAP
T1 - Biosensors-Guided AI Interventions in Personalized Medicines
AU - Naveed, Muhammad
AU - Abid, Amina
AU - Jamil, Hamza
AU - Choudhary, Muhammad Azan Ali
AU - Ali, Syed Murtaza
AU - Rajpoot, Zeerwah
AU - Rana, Irzam Kainat
AU - Asghar, Shumaila
AU - Majeed, Muhammad
AU - Khamparia, Aditya
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Personalized medicine, which focuses on providing individualized healthcare treatments to people based on their unique genetic composition, lifestyle, and environmental circumstances, has emerged as a viable strategy in modern healthcare. Biosensors, which are adaptable analytical instruments capable of detecting biological analytes and turning them into quantifiable signals, play a critical role in personalized medicine. This study presents a complete overview of biosensors’ definition, function, and relevance in the context of personalized medicine, with a focus on their relationship with artificial intelligence (AI) in healthcare. The foundations of biosensors are provided, including their underlying concepts, kinds, and design concerns, paving the way for understanding their applications in personalized medicine. Biosensors enable personalized medicine to accomplish milestones in illness diagnosis, monitoring, medication administration, and therapy response prediction, revolutionizing patient care. Furthermore, the combination of AI with biosensors enables sophisticated data processing, predictive modeling, and real-time monitoring, hence increasing the efficacy and precision of personalized therapies. Despite the potential benefits of biosensor-guided AI treatments in personalized medicine, some problems remain, including ethical considerations, privacy concerns, and technological challenges. However, with continued technical breakthroughs, the future seems promising for overcoming these hurdles and improving the synergy between biosensors and AI in personalized healthcare. The study uses case studies and examples to highlight the practical impact of biosensors and AI integration on patient care and healthcare systems. It also discusses future views and new trends, such as the integration of biosensors into wearable devices and the creation of regulatory frameworks to control their usage in personalized medicine. The study emphasizes the crucial role of biosensor-guided AI treatments in developing personalized medicine, emphasizing the need for ongoing research and development in this sector to realize its full potential in improving patient outcomes and revolutionizing healthcare delivery.
AB - Personalized medicine, which focuses on providing individualized healthcare treatments to people based on their unique genetic composition, lifestyle, and environmental circumstances, has emerged as a viable strategy in modern healthcare. Biosensors, which are adaptable analytical instruments capable of detecting biological analytes and turning them into quantifiable signals, play a critical role in personalized medicine. This study presents a complete overview of biosensors’ definition, function, and relevance in the context of personalized medicine, with a focus on their relationship with artificial intelligence (AI) in healthcare. The foundations of biosensors are provided, including their underlying concepts, kinds, and design concerns, paving the way for understanding their applications in personalized medicine. Biosensors enable personalized medicine to accomplish milestones in illness diagnosis, monitoring, medication administration, and therapy response prediction, revolutionizing patient care. Furthermore, the combination of AI with biosensors enables sophisticated data processing, predictive modeling, and real-time monitoring, hence increasing the efficacy and precision of personalized therapies. Despite the potential benefits of biosensor-guided AI treatments in personalized medicine, some problems remain, including ethical considerations, privacy concerns, and technological challenges. However, with continued technical breakthroughs, the future seems promising for overcoming these hurdles and improving the synergy between biosensors and AI in personalized healthcare. The study uses case studies and examples to highlight the practical impact of biosensors and AI integration on patient care and healthcare systems. It also discusses future views and new trends, such as the integration of biosensors into wearable devices and the creation of regulatory frameworks to control their usage in personalized medicine. The study emphasizes the crucial role of biosensor-guided AI treatments in developing personalized medicine, emphasizing the need for ongoing research and development in this sector to realize its full potential in improving patient outcomes and revolutionizing healthcare delivery.
KW - AI treatment
KW - Biosensors
KW - Neural network
KW - Personalized medicines
UR - https://www.scopus.com/pages/publications/105006793452
U2 - 10.1007/978-981-96-3448-4_10
DO - 10.1007/978-981-96-3448-4_10
M3 - Chapter
AN - SCOPUS:105006793452
T3 - Microorganisms for Sustainability
SP - 185
EP - 208
BT - Microorganisms for Sustainability
PB - Springer
ER -
