The regulatory environment in the United States has not kept pace with the rapidly developing market for artificial intelligence (AI)-enabled devices. The number of AI-enabled devices has increased year after year. All of these devices are registered or cleared by the US Food and Drug Administration through exempt or 510(k) premarket notification pathways, and the majority are related to the radiology or cardiovascular spaces. US Food and Drug Administration guidance has not yet addressed the unique challenges of AI-enabled devices, including development, comprehensibility, and continuously learning models. The liability aspects of AI-enabled devices deployed into use by clinicians in practice have yet to be addressed. Future guidance from government regulatory sources will be necessary as the field moves forward.
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http://dx.doi.org/10.1053/j.semvascsurg.2023.05.005 | DOI Listing |
Bioengineering (Basel)
December 2024
Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, 80125 Naples, Italy.
Diabetes is a chronic condition, and traditional monitoring methods are invasive, significantly reducing the quality of life of the patients. This study proposes the design of an innovative system based on a microcontroller that performs real-time ECG acquisition and evaluates the presence of diabetes using an Edge-AI solution. A spectrogram-based preprocessing method is combined with a 1-Dimensional Convolutional Neural Network (1D-CNN) to analyze the ECG signals directly on the device.
View Article and Find Full Text PDFJ Electrocardiol
January 2025
Department of Emergency Medicine, Hennepin County Medical Center, Hennepin Healthcare, Minneapolis, MN, United States; Department of Emergency Medicine, University of Minnesota School of Medicine, Minneapolis, MN, United States. Electronic address:
Crit Care
January 2025
División de Terapia Intensiva, Hospital Juan A. Fernández, Buenos Aires, Argentina.
The advancements in cardiovascular imaging over the past two decades have been significant. The miniaturization of ultrasound devices has greatly contributed to their widespread adoption in operating rooms and intensive care units. The integration of AI-enabled tools has further transformed the field by simplifying echocardiographic evaluations and enhancing the reproducibility of hemodynamic measurements, even for less experienced operators.
View Article and Find Full Text PDFCureus
November 2024
Neurology, NeuroCareAI, Dallas, USA.
Stroke remains a critical global health challenge, with ischemic stroke comprising most cases and necessitating rapid, effective treatment to improve patient outcomes. This review explores the integration of artificial intelligence (AI) and machine learning into medical devices for stroke triaging, highlighting their impact on reducing notification times, latency in care, and health disparities. By analyzing Food and Drug Administration-approved AI-enabled devices under the "Radiological computer-assisted triage and notification software" regulation category, we assess their sensitivity, specificity, and time-to-notification as the measure of their overall effectiveness in clinical settings.
View Article and Find Full Text PDFSensors (Basel)
December 2024
EXOForce Robotics, Arlington, VA 22209, USA.
Freezing of gait (FOG) is a disabling yet poorly understood paroxysmal gait disorder affecting the vast majority of patients with Parkinson's disease (PD) as they reach advanced stages of the disorder. Falling is one of the most disabling consequences of a FOG episode; it often results in injury and a future fear of falling, leading to diminished social engagement, a reduction in general fitness, loss of independence, and degradation of overall quality of life. Currently, there is no robust or reliable treatment against FOG in PD.
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