AIMC Topic: Artificial Intelligence

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EE-Explorer: A Multimodal Artificial Intelligence System for Eye Emergency Triage and Primary Diagnosis.

American journal of ophthalmology
PURPOSE: To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images.

[Robotics in Liver Surgery - Tips and Tricks].

Zentralblatt fur Chirurgie
Since minimally invasive liver surgery has proven benefits over open surgery, this technique should also be implemented more broadly in Germany. With the dramatic development in minimally invasive and robotic liver surgery, this approach has been est...

A machine learning analysis to evaluate the outcome measures in inflammatory myopathies.

Autoimmunity reviews
OBJECTIVE: To assess the long-term outcome in patients with Idiopathic Inflammatory Myopathies (IIM), focusing on damage and activity disease indexes using artificial intelligence (AI).

Implementation of digital home monitoring and management of respiratory disease.

Current opinion in pulmonary medicine
PURPOSE OF REVIEW: Digital respiratory monitoring interventions (e.g. smart inhalers and digital spirometers) can improve clinical outcomes and/or organizational efficiency, and the focus is shifting to sustainable implementation as an approach to de...

A systematic review of the applications of markerless motion capture (MMC) technology for clinical measurement in rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: Markerless motion capture (MMC) technology has been developed to avoid the need for body marker placement during motion tracking and analysis of human movement. Although researchers have long proposed the use of MMC technology in clinical...

Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model.

Critical care (London, England)
BACKGROUND: Identifying patterns within ICU medication regimens may help artificial intelligence algorithms to better predict patient outcomes; however, machine learning methods incorporating medications require further development, including standar...

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...

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

Radiology
Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)-aided mammography...