Medical device regulations

Gudeppu, Mounika; Sawant, Swaroop; Chockalingam, Chella Ganapathy; Shanmugam, Prakash Srinivasan Timiri

doi:10.1016/b978-0-12-820960-8.00008-3

Cited by 5 publications

(2 citation statements)

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“…Simplifying the explanation of decisionmaking, diagnosis and foundation of operation may enable intelligent supervision to mitigate the clinical risk. The results align with current EU policy and industry body recommendations for the use of AI DHI, including medical devices [16].…”

Section: Discussionsupporting

confidence: 79%

Hazards for the Implementation and Use of Artificial Intelligence Enabled Digital Health Interventions, a UK Perspective

Harrison

Despotou

Arvanitis

2022

Studies in Health Technology and Informatics

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Background: Artificial Intelligence (AI) has seen an increased application within digital healthcare interventions (DHIs). DHIs use entails challenges about their safety assurance. Exacerbated by regulatory requirements, in the UK, this places the onus of safety assurance not only on the manufacturer, but also on the operator of a DHI. Clinical Safety claims and evidencing safe implementation and use of AI-based DHIs require expertise, to understand and act to control or mitigate risk. Current health software standards, regulation, and guidance do not provide the insight necessary for safer implementation. Objective: To interpret published guidance and policy related to AI and justify clinical safety assurance of DHIs. Method: Assessment of UK health regulation policy, standards, and AI institution insights, utilizing a published Hazard Assessment framework, to structure safety justifications, and articulate hazards relating to AI-based DHIs. Results: AI enabled DHI hazard identification, relating to implementation and use within healthcare delivery organizations. Conclusion: By application of the method, we postulate that UK research of AI DHIs highlighted issues that may affect safety, in need of consideration to justify safety of a DHI.

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Section: Discussionsupporting

confidence: 79%

Hazards for the Implementation and Use of Artificial Intelligence Enabled Digital Health Interventions, a UK Perspective

Harrison

Despotou

Arvanitis

2022

Studies in Health Technology and Informatics

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“…Cleanliness is defined as when the number of impurities is below a certain level, and cleaning is the process of removing biological, chemical, and physical contaminants [ 20 , 21 ]. The American Society of Testing and Materials has published a protocol for cleaning surgical implants without solvents [ 22 ]; starting with using alkaline systems to remove oil and lubricants, then followed by sandblasting with high-quality, iron-free silica.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Cleanliness of Dental Implants Using Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy Analysis—A SEM and EDS In Vitro Study

Mtanis

Biadsee

Ormianer

2023

JFB

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A wide variety of titanium (Ti) alloy dental implant systems are available and as a result, choosing the correct system has become a challenge. Cleanliness of the dental implant surface affects osseointegration but surface cleanliness may be jeopardized during manufacturing. The purpose of this study was to assess the cleanliness of three implant systems. Fifteen implants per system were examined with scanning electron microscopy to identify and count foreign particles. Particle chemical composition analysis was performed with energy-dispersive X-ray spectroscopy. Particles were categorized according to size and location. Particles on the outer and inner threads were quantitatively compared. A second scan was performed after exposing the implants to room air for 10 min. Carbon, among other elements, was found on the surface of all implant groups. Zimmer Biomet dental implants had higher particle numbers than other brands. Cortex and Keystone dental implants showed similar distribution patterns. The outer surface had higher particle numbers. Cortex dental implants were the cleanest. The change in particle numbers after exposure was not significant (p > 0.05). Conclusion: Most of the implants studied were contaminated. Particle distribution patterns vary with the manufacturer. The wider and outer areas of the implant have a higher probability of contamination.

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Translation of Wound Devices into Practice—A Myth? Translation is the Process of Taking an Invention Through to Clinical Practice—How Successful Are We?

Richardson¹,

Mani

2023

Chronic Wound Management

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Medical device regulations

Cited by 5 publications

References 0 publications

Hazards for the Implementation and Use of Artificial Intelligence Enabled Digital Health Interventions, a UK Perspective

Hazards for the Implementation and Use of Artificial Intelligence Enabled Digital Health Interventions, a UK Perspective

Assessing the Cleanliness of Dental Implants Using Scanning Electron Microscopy and Energy-Dispersive X-ray Spectroscopy Analysis—A SEM and EDS In Vitro Study

Translation of Wound Devices into Practice—A Myth? Translation is the Process of Taking an Invention Through to Clinical Practice—How Successful Are We?

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