AI Medical Device Safety: Scoping Review with ☸️SAIMSARA.

Name: SAIMSARA Evidence Object digital::AI_MEDICAL_DEVICE_SAFETY_SS
Creator: SAIMSARA
License: https://saimsara.com/license/

SAIMSARA

doi:10.62487/saimsaraa33bf709

Reference Index (146)

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[2] Medical Device Safety: An Analytical International Survey of AI/ML-Enabled Medical Devices — https://doi.org/10.1109/cai64502.2025.00108
[3] AI-Enhanced Predictive Analytics for Quality System Regulation (QSR) Compliance and Defect Minimization in Medical Device Production — https://doi.org/10.1109/icat2i69744.2025.11472723
[4] Feasibility of Using LLMs to Automate Analysis of AI/ML Medical Device Approvals — https://doi.org/10.1145/3774816.3774830
[5] AI-Enhanced Medical Device Software Testing: Improving Efficiency and Coverage — https://doi.org/10.47363/pms/2024(8)e105
[6] Artificial intelligence related safety issues associated with FDA medical device reports — https://doi.org/10.1038/s41746-024-01357-5
[7] AI as a Medical Device Adverse Event Reporting in Regulatory Databases: Protocol for a Systematic Review — https://doi.org/10.2196/48156
[9] Real-Time Edge AI with Explainable Deep Learning for Predictive Maintenance of Medical Devices: *Instantaneous Detection of Medical Device Failures using Edge AI — https://doi.org/10.1109/isiber68248.2026.11470555
[10] A Two-Dimensional Risk Framework for AI in Mental Health Software as a Medical Device — https://doi.org/10.2139/ssrn.6371838
[11] Adversarial Machine Learning Threats To Medical Device AI Controllers — https://doi.org/10.62970/ijirct.v12.i2.2604012
[12] Global Harmonization of Artificial Intelligence-Enabled Software as a Medical Device Regulation: Addressing Challenges and Unifying Standards — https://doi.org/10.1016/j.mcpdig.2024.100191
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[17] Medical Device Failure Prediction Framework — https://doi.org/10.1109/itechsecom64750.2025.11307573
[18] LLM Based Knowledge Graph Approach to Automating Medical Device Regulatory Compliance — https://doi.org/10.1109/bigdata66926.2025.11402139
[20] MedReg-KG: KnowledgeGraph for Streamlining Medical Device Regulatory Compliance — https://doi.org/10.1109/bigdata62323.2024.10825686
[22] Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction — https://doi.org/10.48550/arxiv.2207.05796
[24] Homeyx: A Low-Cost Distributed Physical AI Framework for Multimodal Assistive Robotics with Safety-Constrained Medical Advisory — https://doi.org/10.1109/raeeucci67649.2026.11504476
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[27] Changes in software as a medical device based on artificial intelligence technologies — https://doi.org/10.1007/s11548-022-02669-1
[28] Methodology for Conducting Post-Marketing Surveillance of Software as a Medical Device Based on Artificial Intelligence Technologies — https://doi.org/10.17691/stm2022.14.5.02
[29] A deployment safety case for AI-assisted prostate cancer diagnosis — https://doi.org/10.1016/j.compbiomed.2025.110237
[30] The need for a system view to regulate artificial intelligence/machine learning-based software as medical device — https://doi.org/10.1038/s41746-020-0262-2
[31] Risk Assessment and Classification of Medical Device Software for the Internet of Medical Things: Challenges arising from connected, intelligent medical devices — https://doi.org/10.1145/3567445.3571104
[33] AI-Powered QA in Healthcare Software: Leveraging Predictive Analytics and Digital Twins for Safe, Cost-Effective, and Agile Medical Systems — https://doi.org/10.32996/jcsts.2025.4.1.70
[36] Safe Sound: AI-Based Elderly Sound Safety Monitoring System — https://doi.org/10.47392/irjaeh.2026.0446
[37] Implementation of Industry 4.0 in Transformation of Medical Device Maintenance Systems — https://doi.org/10.4018/978-1-7998-2725-2.ch023
[38] CNN-Based Medical Device Design for the Smart Pillbox With Face Recognition — https://doi.org/10.1109/iccst50977.2020.00125
[39] Diverging regulatory DNA in adaptive medical AI: US agility and EU accountability in lifecycle governance — https://doi.org/10.3389/fmed.2026.1758708
[42] AI regulation in healthcare around the world: what is the status quo? — https://doi.org/10.1101/2025.01.25.25321061
[43] AI-based assessment of Clinical Activity Score and detection of active thyroid eye disease using facial images: validation of Glandy CAS — https://doi.org/10.1136/bmjophth-2025-002264
[50] Predictive Maintenance of Biomedical Devices using AI — https://doi.org/10.1109/isac364032.2025.11156730
[52] Significant Radiation Reduction Using Cloud-Based AI Imaging in Manually Matched Cohort of Complex Aneurysm Repair. — https://doi.org/10.1016/j.avsg.2024.12.081
[60] A Multi-Modal AI Framework for Intrusion Detection in ‎Healthcare IoT — https://doi.org/10.14419/xw7zzh51
[61] Software as Medical Devices: requirements and regulatory landscape in the United States — https://doi.org/10.1080/17434440.2025.2561918
[63] A tool for the assessment of AI generalizability via decision space composition — https://doi.org/10.1117/12.3008580
[68] Systems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices — https://doi.org/10.48550/arxiv.2506.15028
[71] Semantically Rich Approach to Automating Regulations of Medical Devices — https://doi.org/10.1109/icdh62654.2024.00032
[73] Development of a Novel Leader Device with Haptic Feedback for Vascular Interventional Surgery — https://doi.org/10.1109/icma57826.2023.10216120
[74] Stakeholder Perspectives on Early Feasibility Studies for Digital Health Technologies in the European Union: Qualitative Interview Study — https://doi.org/10.2196/77982
[75] An Agentic, Multimodal RAG Framework for Risk-Aware Surgical Robotics User Manual Creation — https://doi.org/10.1109/syscon66367.2026.11503503
[76] A Reliability Evaluation Flow for Assessing the Impact of Permanent Hardware Faults on Integer Arithmetic Circuits — https://doi.org/10.1109/access.2025.3534274
[77] Guardian Alert: One-Tap Emergency Help for Women and Elderly People — https://doi.org/10.4108/eai.28-4-2025.2357919
[80] Edge-Based Computation of Super-Resolution Superlet Spectrograms for Real-Time Estimation of Heart Rate Using an IoMT-Based Reference-Signal-Less PPG Sensor — https://doi.org/10.1109/jiot.2023.3322947
[82] Risks and benefits associated with the primary functions of artificial intelligence powered autoinjectors — https://doi.org/10.3389/fmedt.2024.1331058
[86] P042 Developing a clinical audit methodology for monitoring dermatologist performance in artificial intelligence-enabled teledermatology pathways — https://doi.org/10.1093/bjd/ljae090.069
[87] Towards an AI-driven real time verification of radiotherapy treatments — https://doi.org/10.1109/nss/mic42101.2019.9059742
[89] Autonomous artificial intelligence in classification of screening chest radiographs: clinical and economic feasibility — https://doi.org/10.17816/dd641703
[90] Artificial intelligence-guided automated measurement of pulmonary vein diameter in patients with atrial fibrillation — https://doi.org/10.1093/europace/euad122.538
[91] Evaluation of the impact of assistive artificial intelligence on ultrasound scanning for regional anaesthesia — https://doi.org/10.1016/j.bja.2022.07.049
[92] OSAIRIS: Lessons Learned From the Hospital-Based Implementation and Evaluation of an Open-Source Deep-Learning Model for Radiotherapy Image Segmentation. — https://doi.org/10.1016/j.clon.2024.10.032
[93] Improving the Robustness of Model Compression by On-Manifold Adversarial Training — https://doi.org/10.3390/fi13120300
[97] Evaluating the Safety and Usability of an Over-the-Counter Medical Device for Adults With Mild to Moderate Hearing Loss: Formative and Summative Usability Testing — https://doi.org/10.2196/65142
[99] A scoping review of reporting gaps in FDA-approved AI medical devices — https://doi.org/10.1038/s41746-024-01270-x
[100] The Data Privacy Protection Laws impacting AI Medical Devices in the US, EU, China, Japan, and India — https://doi.org/10.70818/apjmi.v02i03.030
[102] Integrating Explainable Artificial Intelligence into Malaysia’s Medical Device Regulatory Framework: A Preliminary Analysis — https://doi.org/10.47772/ijriss.2025.909000582
[104] User Interface Improvement for Usability Test of Artificial Intelligence-based Software as a Medical Device for Diagnosis of Neovascular Age-related Macular Degeneration — https://doi.org/10.17480/psk.2024.68.2.121
[105] Evaluating transparency in AI/ML model characteristics for FDA-reviewed medical devices — https://doi.org/10.1038/s41746-025-02052-9
[106] Towards provable probabilistic safety for scalable embodied AI systems — https://doi.org/10.48550/arxiv.2506.05171
[108] Clinical Trial Design and Regulatory Requirements for Artificial Intelligence as a Medical Device: A PRISMA-ScR-Guided Scoping Review of Global Guidance and Evidence (2017-2025). — https://doi.org/10.3390/jcm15051937
[109] Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations — https://doi.org/10.48550/arxiv.2505.06620
[110] Securing AI and Agentic Systems in Medical Devices: Methods, Risks, and Defenses — https://doi.org/10.1109/icpeev67897.2025.11291555
[111] Leveraging Digital Twins for Root Cause Analysis in Complex Medical Device Manufacturing — https://doi.org/10.18535/ijmsci/v08i4.05
[112] Post-Market Surveillance of Medical Devices Using AI — https://doi.org/10.9734/jocamr/2024/v25i7552
[115] An AI-Driven Cybersecurity Framework for the Internet of Medical Things: A Hybrid LSTM-CNN-GAN Approach — https://doi.org/10.1109/icmlas64557.2025.10967601
[116] The AI cycle of health inequity and digital ageism: mitigating biases through the EU regulatory framework on medical devices — https://doi.org/10.1093/jlb/lsad031
[120] Health Disparities and Reporting Gaps in Artificial Intelligence (AI) Enabled Medical Devices: A Scoping Review of 692 U.S. Food and Drug Administration (FDA) 510k Approvals — https://doi.org/10.1101/2024.05.20.24307582
[125] Assuring the safety of AI-based clinical decision support systems: a case study of the AI Clinician for sepsis treatment — https://doi.org/10.1136/bmjhci-2022-100549
[126] The concept of predictable harm in development of AI-powered medical devices — https://doi.org/10.24075/medet.2025.006
[127] AI-Driven Cybersecurity Intelligence for Protecting Healthcare Data and Medical IoT Systems — https://doi.org/10.1109/cnc68716.2025.11484971
[129] Thermal management of an interventional medical device with double layer encapsulation — https://doi.org/10.1080/08916152.2021.1946208
[130] Safety and User Experience of a Generative Artificial Intelligence Digital Mental Health Intervention: Exploratory Randomized Controlled Trial — https://doi.org/10.2196/67365
[131] Developing real-time IoT-based public safety alert and emergency response systems — https://doi.org/10.1038/s41598-025-13465-7
[132] Non-Contact Fall Detection System Using 4D Imaging Radar for Elderly Safety Based on a CNN Model — https://doi.org/10.3390/s25113452
[133] MedRoboLegalNet: An AI Framework for Evaluating Medical Negligence and Legal Compliance in Robotic Surgeries — https://doi.org/10.1109/icsft66733.2026.11506669
[134] Generative AI’s healthcare professional role creep: a cross-sectional evaluation of publicly accessible, customised health-related GPTs — https://doi.org/10.3389/fpubh.2025.1584348
[135] Thermal Stress Analysis via Infrared Imaging for Safety Monitoring in Biomedical Electronic Devices — https://doi.org/10.1109/bats67559.2025.11336186
[136] Key Information Influencing Patient Decision-Making About AI in Health Care: Survey Experiment Study — https://doi.org/10.2196/75615
[138] Real-Time Monitoring of Personal Protective Equipment Adherence Using On-Device Artificial Intelligence Models — https://doi.org/10.3390/s25072003
[140] Intelligent Acceleration: Redefining Clinical Trials for Drugs and Devices with AI — https://doi.org/10.53902/cicmr.2025.03.000523
[142] A decade of review in global regulation and research of artificial intelligence medical devices (2015–2025) — https://doi.org/10.3389/fmed.2025.1630408
[143] 1262 Personalizing PAP Comfort Through AI-enabled Modeling: Retrospective Insights and Future Directions — https://doi.org/10.1093/sleep/zsag091.1261
[145] Agentic AI for Healthcare Cybersecurity: Autonomous Threat Detection and Ethical Implementation Challenges — https://doi.org/10.1109/imed68921.2026.11484331
[147] AI-DRIVEN PREDICTIVE MAINTENANCE FOR HIGH-VOLTAGE X-RAY CT TUBES: A MANUFACTURING PERSPECTIVE — https://doi.org/10.63125/npwqxp02
[148] AI-Enabled Monitoring of Space Robotics Telemetry — https://doi.org/10.65391/r3341
[149] Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights — https://doi.org/10.1145/3676536.3676804
[151] Artificial Intelligence–Enabled Intensive Care Unit (AI‑ICU): Integrated Framework for Real‑Time Decision Support, Automated Clinical Handoffs, and Intelligent Wound Monitoring — https://doi.org/10.36948/ijfmr.2025.v07i06.63700
[154] Developing a Generative AI-Powered Chatbot for Analyzing MAUDE Database — https://doi.org/10.3233/shti240639
[156] A Cloud-Edge Microservices Architecture for Smart Healthcare: SDN-Based Medical Asset Management — https://doi.org/10.1109/memea65319.2025.11067988
[160] Cardio Rescue Network in AI-Driven Wearable System for Real-Time Cardiac Event Prediction and Management Using 5G-Enabled Edge Computing — https://doi.org/10.1109/sennet64220.2025.11135976
[161] Image-Based Zero-Day Malware Detection in IoMT Devices: A Hybrid AI-Enabled Method — https://doi.org/10.1109/isqed57927.2023.10129348
[164] Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses — https://doi.org/10.48550/arxiv.2310.18494
[167] How threshold customisation affects the performance of a multiclass X-ray AI model for primary care triage: a retrospective study — https://doi.org/10.1136/bmjopen-2025-111127
[168] Benefit-Risk Reporting for FDA-Cleared Artificial Intelligence−Enabled Medical Devices — https://doi.org/10.1001/jamahealthforum.2025.3351
[169] Dual-Mode Deep Anomaly Detection for Medical Manufacturing: Structural Similarity and Feature Distance — https://doi.org/10.48550/arxiv.2509.05796
[170] Deep Learning-Based SBOM Defect Detection for Medical Devices — https://doi.org/10.1109/icaiic60209.2024.10463483
[171] Real-Time Identification of Look-Alike Medical Vials Using Mixed Reality-Enabled Deep Learning — https://doi.org/10.3390/fi17050223
[172] Formation of the market of software medical devices in the Russian Federation in 2007–2024: Practical results — https://doi.org/10.47093/2713-069x.2024.5.3.53-61
[173] Mitigating Ransomware Attacks in Internet of Medical Things Networks — https://doi.org/10.1109/icsc65596.2025.11140094
[175] Safeguarding Connected Health: Leveraging Trustworthy AI Techniques to Harden Intrusion Detection Systems Against Data Poisoning Threats in IoMT Environments — https://doi.org/10.58496/bjiot/2023/005
[177] Clinical Effectiveness of an Artificial Intelligence-Based Prediction Model for Cardiac Arrest in General Ward-Admitted Patients: A Non-Randomized Controlled Trial — https://doi.org/10.3390/diagnostics16020335
[179] Med-Aligner empowers LLM medical applications for complex medical scenarios — https://doi.org/10.1016/j.xinn.2025.101002
[181] An Explainable Deep Learning-Based Predictive Maintenance Solution for Air Compressor Condition Monitoring — https://doi.org/10.3390/s25185797
[182] Implementing Real-Time VR Simulations for Complex Surgical Training — https://doi.org/10.1109/ietacs68750.2025.11385343
[183] Federated learning: a privacy-preserving approach to data-centric regulatory cooperation — https://doi.org/10.3389/fdsfr.2025.1579922
[184] BedEye: A Bed Exit and Bedside Fall Warning System Based on Skeleton Recognition Technology for Elderly Patients — https://doi.org/10.1109/access.2025.3558004
[185] Shape Prior for Quality Assessment in OCTA via Denoising Autoencoders at the Segmentation Level — https://doi.org/10.1109/access.2025.3625745
[187] Robotic Arm Control System Based on AI Wearable Acceleration Sensor — https://doi.org/10.1155/2021/5544375
[197] SG-VAE: Explainable Semi-Generative Model for Attack Detection in IoT Healthcare Systems — https://doi.org/10.1109/wimob66857.2025.11257554
[198] Leveraging the smarts in your phone: An artificial intelligence-driven iOS application for neurosurgical navigation of external ventricular drains — https://doi.org/10.36922/aih.8195
[199] Blockchain-integrated IoT framework for tamper-proof healthcare data management in smart hospitals — https://doi.org/10.55529/ijitc.61.56.66
[201] Enhancing IoMT Security with Explainable Machine Learning: A Case Study on the CICIOMT2024 Dataset — https://doi.org/10.48550/arxiv.2509.10563
[202] An embedded clinical decision support system for OCT — https://doi.org/10.1117/12.3039047
[217] IOT ENABLED CARDIAC HEALTH MONITORING AND EMERGENCY ALERT SYSTEM — https://doi.org/10.55041/ijsrem45038
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[225] Design and performance evaluation of a green LED OFDM LiFi system for an electromagnetic interference sensitive hospital network — https://doi.org/10.1007/s10791-026-09906-0
[226] Wearable Biosensors and AI Analytics for Continuous Health Monitoring and Early Disease Detection — https://doi.org/10.59675/e225
[229] Pareto-Optimal Model Selection for Low-Cost, Single-Lead EMG Control in Embedded Systems — https://doi.org/10.48550/arxiv.2601.06516
[230] Enhancing mechanical ventilator reliability through machine learning based predictive maintenance — https://doi.org/10.1177/09287329241301665
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[252] MedGlasses: A Wearable Smart-Glasses-Based Drug Pill Recognition System Using Deep Learning for Visually Impaired Chronic Patients — https://doi.org/10.1109/access.2020.2967400
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[256] RISCNet: A Novel Deep Learning Model for Real-Time Radiation induced sickness Classification — https://doi.org/10.1109/imcet69180.2026.11503747
[258] Empowering Clinical Engineering and Evidence-Based Maintenance with IoT and Indoor Navigation — https://doi.org/10.3390/fi16080263
[259] Improving medication error classification using a reasoning large language model — https://doi.org/10.1093/jamiaopen/ooag004
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[264] Explainable ECG Beat Classification On The Edge for Smart, Trustworthy and Low-Power Wearables — https://doi.org/10.1109/biocas58349.2023.10389065
[267] Unveiling Healthcare Professionals’ Perspectives through a Knowledge, Attitude, and Practice Study on Artificial Intelligence in Materiovigilance – An Interventional Study — https://doi.org/10.4103/ajprhc.ajprhc_130_25
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[272] Single-Use Autoinjector Functionality And Reliability For At-Home Administration Of Benralizumab For Patients With Severe Asthma: GRECO Trial Results — https://doi.org/10.2147/JAA.S224266
[273] Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study — https://doi.org/10.2196/18097
[274] Fuzzy Based Multimodality Clinical Alarm in ICU/CCU — https://doi.org/10.1109/iche55634.2022.10179878
[280] New Encapsulation Concepts for Medical Ultrasound Probes-A Heat Transfer Simulation Study — https://doi.org/10.23919/empc44848.2019.8951832
[282] Intervention design for artificial intelligence-enabled macular service implementation: a primary qualitative study — https://doi.org/10.1186/s43058-024-00667-9
[283] Multi-Layered Unsupervised Learning Driven by Signal-to-Noise Ratio-Based Relaying for Vehicular Ad Hoc Network-Supported Intelligent Transport System in eHealth Monitoring — https://doi.org/10.3390/s24206548
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AI Medical Device Safety: Scoping Review with ☸️SAIMSARA.

Digital Health

Issue 3, Volume 1, 2026

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