AIMC Topic: Point-of-Care Systems

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Development of a Novel Fluorescent-Based Lateral Flow Assay for the Detection of Neisseria gonorrhoeae at the Point of Care.

Sexually transmitted diseases
BACKGROUND: Neisseria gonorrhoeae (NG) has acquired significant resistance, primarily due to extensive and unwarranted antibiotic utilization over several decades. This resistance has largely been associated with the syndromic management of sexually ...

Essential Point-of-Care Ultrasound Insights for 2024.

Seminars in ultrasound, CT, and MR
To assess point-of-care ultrasound (POCUS) in 2024, we should start by defining its expanded scope and integration into general and specialty practice. Clinicians should abide by the evolving evidence for POCUS utilization and patient outcomes differ...

Empowering Medical Students: Harnessing Artificial Intelligence for Precision Point-of-Care Echocardiography Assessment of Left Ventricular Ejection Fraction.

International journal of clinical practice
INTRODUCTION: Point-of-care ultrasound (POCUS) use is now universal among nonexperts. Artificial intelligence (AI) is currently employed by nonexperts in various imaging modalities to assist in diagnosis and decision making.

Deep learning enabled fast 3D brain MRI at 0.055 tesla.

Science advances
In recent years, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications. However, its quality is poor and scan time is long. We propose a fast a...

Mitigating bias in AI at the point of care.

Science (New York, N.Y.)
Promoting equity in AI in health care requires addressing biases at cli nical implementation.

Health system-scale language models are all-purpose prediction engines.

Nature
Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by forecasting clinical and operational events. Existing structured data-based clinical predictive models ...

The Gap Between AI and Bedside: Participatory Workshop on the Barriers to the Integration, Translation, and Adoption of Digital Health Care and AI Startup Technology Into Clinical Practice.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) and digital health technological innovations from startup companies used in clinical practice can yield better health outcomes, reduce health care costs, and improve patients' experience. However, the integrat...

Deep Learning-Enabled Multiplexed Point-of-Care Sensor using a Paper-Based Fluorescence Vertical Flow Assay.

Small (Weinheim an der Bergstrasse, Germany)
Multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury is demonstrated. This point-of-care sensor includes a paper-based fluorescence vertical flow assay (fxVFA) ...

AI-ENABLED ASSESSMENT OF CARDIAC FUNCTION AND VIDEO QUALITY IN EMERGENCY DEPARTMENT POINT-OF-CARE ECHOCARDIOGRAMS.

The Journal of emergency medicine
BACKGROUND: The adoption of point-of-care ultrasound (POCUS) has greatly improved the ability to rapidly evaluate unstable emergency department (ED) patients at the bedside. One major use of POCUS is to obtain echocardiograms to assess cardiac functi...

Multiplex Identification of Post-Translational Modifications at Point-of-Care by Deep Learning-Assisted Hydrogel Sensors.

Angewandte Chemie (International ed. in English)
Multiplex detection of protein post-translational modifications (PTMs), especially at point-of-care, is of great significance in cancer diagnosis. Herein, we report a machine learning-assisted photonic crystal hydrogel (PCH) sensor for multiplex dete...