The Future of Personalized Medicine and Internet of Things Reshaping Healthcare Treatment Plans and Patient Experiences


 

Tan lan Hong1, Yagnik Dave2, Ankur Khant3, Lokesh Verma4, Megha Chauhan5, S Parthasarathy6,*

 

1Senior lecturer, Universiti Teknikal Malaysia Melaka (UTeM), Faculty of Technology Management & Technopreneurship (FPTT), Department of Technology Management, Malaysia

2Assistant professor, Department of Physiotherapy, Faculty of Physiotherapy Marwadi University. India

3Associate professor, Department of Physiotherapy, Faculty of Physiotherapy Marwadi University, India

4Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India

5Assistant Professor, Department of Law, Symbiosis Law School, NOIDA-Symbiosis International (Deemed University), Pune, India

6Professor, Department of anesthesiology, Mahatma Gandhi Medical College and Research Institute, Sri Balaji Vidyapeeth (deemed university) Pondicherry, India

Text Box: Abstract The article "The Future of Personalized Medicine and How the Healthcare Internet of Things is Reshaping Treatment Plans and Patient Experiences" offers a comprehensive exploration of the transformative landscape of healthcare. The introduction highlights the paradigm shift from a generalized approach to personalized medicine, where treatments are tailored to individual genetic and lifestyle profiles. Leveraging advanced data analytics and the Healthcare Internet of Things (IoT), the study investigates the impact of these technologies on treatment plans and patient experiences. Employing a multifaceted approach, the research integrates various methods, including logistic regression, random forest, support vector machines, neural networks, and time series analysis, to assess their efficacy in reshaping healthcare practices. Evaluation metrics, such as accuracy, sensitivity, specificity, F1 score, computational cost, and data security, are employed to compare the proposed method with traditional approaches, revealing the superiority of the proposed method across multiple parameters. The results demonstrate the transformative potential of personalized medicine and the Healthcare IoT in enhancing healthcare outcomes and patient experiences. For instance, the proposed method achieves an accuracy of 95%, significantly surpassing traditional methods that average around 89%. Sensitivity, a critical metric in healthcare, reaches 92%, demonstrating the proposed method's ability to identify true positives with higher precision. Additionally, the computational cost of the proposed method, at 0.015, is notably more efficient than traditional methods, which range from 0.020 to 0.022. These numerical values underscore the superior performance of the proposed method, highlighting the importance of integrating cutting-edge technologies for optimized patient care. In conclusion, the study underscores the imperative of embracing a patient-centric approach in healthcare. Emails: layhong@utem.edu.my; yagnik.dave@marwadieducation.edu.in; ankurkumar.khant@marwadieducation.edu.in; lokesh.verma.orp@chitkara.edu.in; megha@symlaw.edu.in; painfreepartha@gmail.com

Received: February 21, 2024 Revised: April 30, 2024 Accepted: July 22, 2024

Keywords: Analytics; Healthcare; Internet; Medicine; Personalized; Plans; Reshaping; Technology; Treatment; IoT