International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Custom AI Protocols for Post-Surgical Recovery

Author(s) Mr. Ritheshh J
Country India
Abstract Post-surgical recovery plays a crucial role in determining patient outcomes, yet traditional recovery protocols often fail to account for the individual variations in patient response. These standardized approaches can lead to longer recovery times, increased complications, and lower patient satisfaction. Artificial Intelligence (AI) offers a promising solution to these challenges by enabling personalized, data-driven recovery plans that can be dynamically adjusted based on real-time patient data. This paper explores the role of AI in transforming post-surgical recovery, focusing on the development and implementation of custom AI protocols.
AI systems can integrate data from various sources such as wearable devices, electronic health records (EHRs), and mobile health applications to monitor key recovery metrics like pain levels, mobility, and wound healing. By continuously analyzing these data points, AI can tailor recovery protocols to individual patients, optimizing treatment plans, improving adherence, and predicting potential complications. This dynamic approach has the potential to reduce recovery time, prevent readmissions, and enhance overall patient satisfaction.
However, the integration of AI in post-surgical recovery also presents challenges, including concerns about data privacy, algorithmic bias, and the need for clinical validation. Ethical considerations regarding informed consent and transparency are also discussed. The paper concludes by exploring future directions for AI in healthcare, including the integration of AI with robotic surgery, telehealth platforms, and the development of regulatory frameworks to ensure the safe and equitable adoption of AI in recovery protocols.
Field Computer Applications
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-14
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.41427
Short DOI https://doi.org/g9fm3p
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E-ISSN 2582-2160
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