Abstract
Our modern world is marked by rapid progress in Information and Communication Technologies (ICTs). Though there are limitations of the digital divide globally, the use of Artificial intelligence (AI) has revolutionized the healthcare industry through predictive analytics and the integration of healthcare Internet of Things (IoT) devices. Predictive healthcare analytics, integrated with explainable AI (XAI), can improve the efficiency and effectiveness of healthcare delivery. Healthcare IoT (HIoT) devices provide the data for predictive analytics and enable remote monitoring of patients. Predictive healthcare analytics can identify high-risk patients for chronic conditions and develop personalized treatment plans. AI can analyze patient data, including demographic information, medical history, and lab test results, to identify patterns and predict future health outcomes leading to better intervention. Patients at high risk for acute conditions can be helped, thus reducing the overall cost of care and improving patient prognoses. HIoT devices, provide information on patient vital signs, physical activity, and medication adherence. Wearable fitness trackers, such as smartwatches and fitness bands, provide data on physical activity and sleep patterns to identify patients at risk for chronic conditions such as heart disease. Remote monitoring devices can provide real-time data on patient vital signs, enabling healthcare professionals to monitor patients remotely within a hospital environment and care facilities and intervene as needed. A well-integrated secure ecosystem with seamless wireless connectivity can usher in innovative AI-based healthcare solution.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
International Telecommunication Union https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx. Accessed 11 Feb 2023
Van Dijk JA (2006) Digital divide research, achievements and shortcomings. Poetics 34(4–5):221–235
Lopes MA et al (2015) Handling healthcare workforce planning with care: where do we stand? Human Resour Health 13:1–19
World Health Organization https://www.who.int/news/item/02-06-2022-global-strategy-on-human-resources-for-health--workforce-2030
Saeed SA et al (2021) Disparities in health care and the digital divide. Curr Psychiatry Rep 23:1–6
Andresen SL (2002) John McCarthy: father of AI. IEEE Intell Syst 17(5):84–85
Tjoa E, Guan C (2020) A survey on explainable artificial intelligence (xai): toward medical xai. IEEE Trans Neural Netw Learn Syst 32(11):4793–4813
Hameed I et al (2022) Based-xai: breaking ablation studies down for explainable artificial intelligence. arXiv preprint arXiv:2207.05566
Xu X et al (2021) Industry 4.0 and industry 5.0—inception, conception and perception. J Manuf Syst 61:530–535
European Union https://op.europa.eu/en/publication-detail/-/publication/468a892a-5097-11eb-b59f-01aa75ed71a1/. Accessed 11 Feb 2023
Mbunge E et al (2021) Sensors and healthcare 5.0: transformative shift in virtual care through emerging digital health technologies. Global Health J 5(4):169–177
Gupta R et al (2021) GaRuDa: a blockchain-based delivery scheme using drones for healthcare 5.0 applications. IEEE Internet Things Mag 4(4):60–66
Gohar AN et al (2022) A patient-centric healthcare framework reference architecture for better semantic interoperability based on blockchain, cloud, and iot. IEEE Access 10:92137–92157
Miah SJ et al (2020) Methodologies for designing healthcare analytics solutions: a literature analysis. Health Inf J 26(4):2300–2314
Kuvvetli Y et al (2021) A predictive analytics model for covid-19 pandemic using artificial neural networks. Decis Anal J 1:100007
Bastani H, Shi P (2020) Proceed with care: integrating predictive analytics with patient decision-making. https://hamsabastani.github.io/proceedwithcare.pdf. Accessed 11 Feb 2023
Serpush F et al (2022) Wearable sensor-based human activity recognition in the smart healthcare system. Comput Intell Neurosci 2022(1391906)
Belfiore A (2022) IoT in healthcare: a scientometric analysis. Technol Forecast Soc Change 184(122001)
Qadri YA et al (2020) The future of healthcare internet of things: a survey of emerging technologies. IEEE Commun Surv Tutor 22(2):1121–1167
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Chaudhari, A., Sarode, V., Udtewar, S., Moharkar, L., Patil, L., Barreto, F. (2023). A Review of Artificial Intelligence for Predictive Healthcare Analytics and Healthcare IoT Applications. In: Balas, V.E., Semwal, V.B., Khandare, A. (eds) Intelligent Computing and Networking. IC-ICN 2023. Lecture Notes in Networks and Systems, vol 699. Springer, Singapore. https://doi.org/10.1007/978-981-99-3177-4_42
Download citation
DOI: https://doi.org/10.1007/978-981-99-3177-4_42
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-3176-7
Online ISBN: 978-981-99-3177-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)