TY - CHAP
T1 - E-Healthcare Data Management Using Machine Learning and IoT
AU - Titus, Anoop
AU - Denny, Alosh
AU - Sivarajkumar, Sonish
AU - Koyilot, Mufeeda Chemban
AU - Prakash, Gayatri
AU - Nandakumar, Varshni
AU - Shameer, Zarina
AU - Khader, Shameer
AU - Yadav, Kamlesh K.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - This chapter investigates the transformative potential of amalgamating Electronic Health Records (EHRs) with Internet of Things (IoT) sensors and machine learning (ML) in remote healthcare environments. It scrutinizes how interconnected devices enable real-time data acquisition thereby, fostering continuous monitoring and tailored patient care delivery. Through a detailed exploration of innovative EHR-IoT-ML integration, encompassing biometrics and remote diagnostics, it delineates the capabilities for early disease detection, predictive analytics, and refined clinical decision-making. Additionally, it addresses critical aspects of data management strategies and security protocols, imperative for preserving patient confidentiality and ensuring system robustness. By providing elucidative examples and meticulous analysis of challenges and opportunities, this chapter propels forward a trajectory toward a future where technology optimizes remote healthcare delivery, augments patient outcomes, and widens accessibility to vital medical services.
AB - This chapter investigates the transformative potential of amalgamating Electronic Health Records (EHRs) with Internet of Things (IoT) sensors and machine learning (ML) in remote healthcare environments. It scrutinizes how interconnected devices enable real-time data acquisition thereby, fostering continuous monitoring and tailored patient care delivery. Through a detailed exploration of innovative EHR-IoT-ML integration, encompassing biometrics and remote diagnostics, it delineates the capabilities for early disease detection, predictive analytics, and refined clinical decision-making. Additionally, it addresses critical aspects of data management strategies and security protocols, imperative for preserving patient confidentiality and ensuring system robustness. By providing elucidative examples and meticulous analysis of challenges and opportunities, this chapter propels forward a trajectory toward a future where technology optimizes remote healthcare delivery, augments patient outcomes, and widens accessibility to vital medical services.
KW - Clinical decision support systems
KW - Fast healthcare interoperability resources
KW - Health level 7
KW - Internet of medical things
KW - Remote patient monitoring
KW - Wearable devices
UR - http://www.scopus.com/inward/record.url?scp=85203045485&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-5624-7_5
DO - 10.1007/978-981-97-5624-7_5
M3 - Chapter
AN - SCOPUS:85203045485
T3 - Studies in Computational Intelligence
SP - 167
EP - 199
BT - Studies in Computational Intelligence
PB - Springer Science and Business Media Deutschland GmbH
ER -