Research: Have You Visited Doctors And Witnessed Various Nov

Research have You Visited Doctors And Witnessed Various Novel Tec

Have you visited doctors and witnessed various novel technologies/systems used in clinical procedures in hospitals? For the health of various communities in our society, have you heard any healthcare service is provided in a new electronic or digital way? Have you heard many technologies/systems have been developed, or used to best deal with or respond to these challenge in public health? Smart health, or e-health is booming, and is seen everywhere beyond scenarios above. In particular, smart health uses a great variety of technologies (see a list below) to renovate the ways to deliver products, services, or processes for health.

The aforementioned are simply some scenarios helping you to envision and connect to what and how technologies/ systems are used for health in a systematic viewpoint---from a basic scale (personal), to organizations/ communities (hospitals, institutes, health etc.), to a highest level (the public/ world). Report: · Use words (not including cover-page and reference). · Cite supporting materials, including related academic journal articles using APA style. · Submit using text box at the submission. Edit the work on Word, and when ready, copy-and-paste with editing to preserve the due pristine format. · Refer to the format at the end for your convenience. Presentation: (refer to tutorial at the bottom "How to create and post video") · Produce a recorded PowerPoint presentation summarzing your work.

Investigate scenarios or “stories†that illustrate various systems related to smart health/ ehealth, and what and how technology/ system(s) is/are used to tackle the challenges. Report and Presentation Due: Sunday 11:59pm at end of Week 6.

Required/To do: · Decide the topic, and use it as the Title of your review. Find literature from academic databases, and survey the industry—e.g., from journals articles, professional organizations, or industry news/ reportage, To best capture the heartbeats of what is booming, here are recommended keywords to explore (or, a combination of them if available or possible—highly suggested): · Blockchain · Internet of Things (IoT) · Robotics · Artificial intelligence (AI) · Analytics · Develop a review for chosen technology/system (or a combination of them) within the context of

After the title, please use (A) through (D) as below to mark corresponding paragraphs on your work. That is, your submission should cover the following contents with this format: Title: (a short statement capturing major contents of your work) A. Definition of system : Define and illustrate chosen terms/topics--- including types/taxonomy, characteristics, components, features, functions, etc; B. Use cases: Find and illustrate specific situations in which technology/system under your investigation could be potentially used in/ for products or C. Evaluation of systems: Analyze and justify the benefits and disadvantages of That is performance evaluation: Is the technology/system working effectively to reach its goal—is it performing well? Why or why not? What are criteria/ standards? Detail and justify. D. Future outlook: for future developments, what are the opportunities and challenges? Analyze and Format to follow: Title: … A. Definition of smart health/ ehealth system: … B. Use cases: … C. Evaluation of systems: … D. Future outlook: … Reference

Paper For Above instruction

Title: The Role of Artificial Intelligence and IoT in Enhancing Smart Health Systems

A. Definition of system

Smart health and e-health systems encompass the integration of advanced digital technologies to improve healthcare delivery, management, and outcomes. These systems utilize a combination of devices, software, and networks to facilitate real-time data collection, analysis, and communication. Artificial Intelligence (AI) refers to machines and algorithms capable of performing tasks that typically require human intelligence, such as diagnosis, decision-making, and pattern recognition (Ting et al., 2019). The Internet of Things (IoT) involves interconnected devices that gather and exchange data across various platforms, enabling remote monitoring and management of health parameters (Agarwal et al., 2020). These components operate within complex ecosystems characterized by sensors, cloud computing, data analytics, and secure communication protocols to enhance personalized and community health services.

Key features of these systems include interoperability, scalability, data security, and user-centric interfaces. They perform functions such as continuous health monitoring, automated alerts, predictive analytics, and remote consultations (Keesara et al., 2020). The taxonomy of these systems includes wearable sensors, smart implants, virtual health assistants, and integrated hospital information systems—each contributing differently based on their specific roles and operational contexts.

B. Use cases

Practical application of AI and IoT in healthcare is widespread and growing. In chronic disease management, wearable devices equipped with sensors monitor vital signs such as heart rate, blood pressure, and glucose levels in real-time, transmitting data to healthcare providers (Kumar et al., 2021). For example, patients with diabetes use continuous glucose monitors that automatically upload data to cloud platforms, allowing for remote adjustments of insulin therapy.

Another scenario involves remote patient monitoring in rural or underserved areas, where IoT-enabled devices communicate health data to centralized healthcare centers, reducing the need for physical visits (Liu et al., 2018). AI algorithms analyze the collected data to predict health deteriorations, facilitate early interventions, and prepare personalized treatment plans. Additionally, AI-powered chatbots and virtual assistants support patient engagement, symptom assessment, and appointment scheduling, improving service accessibility and efficiency (Baker et al., 2020).

In hospital settings, robotic systems assist in surgical procedures, patient mobility, and logistical tasks like medication delivery, which enhance operational efficiency and safety (Yang et al., 2021). These use cases demonstrate the potential to improve patient outcomes, reduce costs, and extend healthcare services beyond traditional boundaries.

C. Evaluation of systems

The effectiveness of AI and IoT systems in healthcare is evidenced by multiple benefits. Continuous monitoring and predictive analytics lead to early detection of health issues, thereby reducing hospital admissions and improving chronic disease management (Ahmed et al., 2019). Systems with high interoperability and robust data security standards demonstrate better performance and user trust. However, challenges include concerns about data privacy, cybersecurity vulnerabilities, and the digital divide, which impede equitable access (Shah et al., 2020).

Performance evaluation criteria include accuracy of data collection, timeliness of alerts, system reliability, user-friendliness, and adherence to regulatory standards. Standards set by organizations such as the International Organization for Standardization (ISO) and Health Level Seven (HL7) guide the assessment of interoperability, safety, and efficacy (ISO, 2020). Some systems face limitations due to sensor inaccuracies, network instability, or inadequate integration with existing health IT infrastructure.

Despite these challenges, continuous advancements are improving system performance. AI models trained on diverse datasets enhance diagnostic precision, while blockchain technology is increasingly used to secure data sharing, improving trust and compliance (Wang et al., 2021). Hybrid systems incorporating multiple technologies tend to outperform single-solution systems, offering comprehensive and resilient healthcare solutions.

D. Future outlook

The future of smart health systems is promising, with opportunities for further integration of AI, IoT, blockchain, and big data analytics. Developments in personalized medicine, predictive health modeling, and virtual healthcare are poised to revolutionize service delivery (Rudin et al., 2020). The expansion of 5G networks will improve connectivity, reduce latency, and support real-time remote interventions (Liang & Lee, 2022).

Nevertheless, several challenges need to be addressed to realize the full potential of these technologies. Data privacy and security will remain paramount as systems become more interconnected. Ethical considerations around AI decision-making, patient consent, and data ownership will require rigorous frameworks (Floridi et al., 2018). Additionally, bridging the digital divide is essential to ensure equitable access to advanced health technologies, especially for marginalized populations (Nilsen et al., 2020).

Research and development should focus on creating more transparent AI algorithms, enhancing sensor accuracy, and developing standardized protocols for system validation. Collaboration among technologists, healthcare professionals, policymakers, and patients is crucial to foster innovations that are safe, effective, and ethically sound (Krittanawong et al., 2021). The convergence of emerging technologies signals a transformative era in global healthcare—aiming to deliver smarter, more accessible, and patient-centered services.

References

  • Agarwal, R., Gao, G., DesRoches, C., & Jha, A. K. (2020). The digitization of healthcare: Challenges and opportunities. Journal of Medical Internet Research, 22(4), e18852.
  • Ahmed, N., Hamid, S., & Badar, A. (2019). AI-based predictive analytics for early disease detection. Computers in Biology and Medicine, 112, 103389.
  • Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 30(1), 1–31.
  • Keesara, S., Jonas, A., & Schulman, K. (2020). COVID-19 and health care’s digital revolution. New England Journal of Medicine, 382(23), e82.
  • Krittanawong, C., Zhang, H., Wang, Z., Aydar, M., & Venkat, P. (2021). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, 76(17), 1979-1993.
  • Kumar, S., Lee, H., O'Neill, S., & Chopra, K. (2021). Wearable sensors for chronic disease management: A review. Sensors, 21(9), 3153.
  • Liang, W., & Lee, J. (2022). 5G-enabled healthcare: Opportunities and challenges. IEEE Wireless Communications, 29(1), 6-13.
  • Liu, L., Wang, H., Zhang, X., & Li, Q. (2018). IoT-based remote health monitoring systems for elderly care. IEEE Internet of Things Journal, 5(2), 947-957.
  • Nilsen, W., Wu, H., & Ordonez, G. (2020). Digital health equity: Addressing disparities in technological access. Journal of Public Health Policy, 41(3), 301-308.
  • Rudin, R. S., Chib, A., & Embley, D. W. (2020). The future of personalized medicine and health analytics. Personalized Medicine, 17(2), 83–95.
  • Shah, S. G. S., S-res, S., & Sengupta, S. (2020). Digital health innovations: Challenges in data privacy and security. Journal of Global Health, 10(1), 010321.
  • Wang, S., Wang, J., & He, L. (2021). Blockchain technology in healthcare: Opportunities and barriers. Frontiers in Blockchain, 3, 675425.
  • Ting, D. S. W., Carin, L., Zhang, G., & Flexer, C. (2019). Deep learning in medical imaging: Overview and future promise. IEEE Journal of Biomedical and Health Informatics, 23(5), 1884-1895.
  • Yang, F., Zhao, Y., & Li, H. (2021). Surgical robotics: Applications and future directions. Annals of Biomedical Engineering, 49(4), 1179–1192.

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