Proposed Framework for Modifications to Artificial Intelligence/Machine Learning (Ai/Ml)-Based Software as A Medical Device (SAMD)

The rapid adoption of software as a medical device (SAMD) driven by artificial intelligence and machine learning has brought about a fundamental shift in the medical industry. This shift has the potential to greatly improve clinical outcomes and the quality of care provided to patients. This shift has been responsible for a number of key achievements made in recent times. When seen in this context, the proposed legal framework for revisions to the AI/ML-SAMD appears as an essential response to the malleability of these technologies. To successfully navigate the tough process of modifying AI/ML-SAMD with the assistance of this framework. It does this by taking into consideration the need for rapid regulatory scrutiny and making an attempt to combine the promotion of innovation with the simultaneous preservation of patient safety. In other words, it ensures that patient safety is protected while also encouraging innovation. This abstract provides a summary of the fundamental components of the framework, as well as a discussion of the significance of those components with regard to fostering the development of moral AI/ML-SAMD within the context of the healthcare ecosystem. The healthcare sector is undergoing a change as a direct result of artificial intelligence and machine learning, which are improving patient outcomes, diagnostic accuracy, and treatment options. The research emphasizes the significance of specific AI and ML applications as well as the sector’s embrace of this paradigm-shifting technology. In addition, the regulatory framework that has been presented is an important step towards guaranteeing the safe use of AI and ML in the medical field.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/ic3i61595.2024.10829073
Citations
7
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
2.44
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article

Proposed Framework for Modifications to Artificial Intelligence/Machine Learning (Ai/Ml)-Based Software as A Medical Device (SAMD)

Anurag Shrivastava, Munugapati Bhavana, Yogendra Kumar, Upma Jain et al.
7 citations
IoT and Edge/Fog Computing
2.44
article

Proposed Framework for Modifications to Artificial Intelligence/Machine Learning (Ai/Ml)-Based Software as A Medical Device (SAMD)

Anurag Shrivastava, Munugapati Bhavana, Yogendra Kumar, Upma Jain, Mohammed Al‐Farouni, R J Anandhi
article en
7 citations

Abstract

The rapid adoption of software as a medical device (SAMD) driven by artificial intelligence and machine learning has brought about a fundamental shift in the medical industry. This shift has the potential to greatly improve clinical outcomes and the quality of care provided to patients. This shift has been responsible for a number of key achievements made in recent times. When seen in this context, the proposed legal framework for revisions to the AI/ML-SAMD appears as an essential response to the malleability of these technologies. To successfully navigate the tough process of modifying AI/ML-SAMD with the assistance of this framework. It does this by taking into consideration the need for rapid regulatory scrutiny and making an attempt to combine the promotion of innovation with the simultaneous preservation of patient safety. In other words, it ensures that patient safety is protected while also encouraging innovation. This abstract provides a summary of the fundamental components of the framework, as well as a discussion of the significance of those components with regard to fostering the development of moral AI/ML-SAMD within the context of the healthcare ecosystem. The healthcare sector is undergoing a change as a direct result of artificial intelligence and machine learning, which are improving patient outcomes, diagnostic accuracy, and treatment options. The research emphasizes the significance of specific AI and ML applications as well as the sector’s embrace of this paradigm-shifting technology. In addition, the regulatory framework that has been presented is an important step towards guaranteeing the safe use of AI and ML in the medical field.

Horizon College and Seminary (CA), Iraqi University (IQ), Birla Institute of Technology and Science - Hyderabad Campus (IN), Graphic Era University (IN), GLA University (IN), Saveetha University (IN)
Openalex Percentile: Top 10%
IoT and Edge/Fog Computing
2.44
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