AIMC Topic: Conscious Sedation

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Machine learning-based prediction of respiratory depression during sedation for liposuction.

Scientific reports Jun 4, 2025
Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early detection of respiratory compromise could not only enhance patient safety during procedural sedation...
Female Aged Adult Humans Machine Learning Respiratory Insufficiency Conscious Sedation Lipectomy Middle Aged Body Composition Male
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Augmenting patient monitoring during intravenous moderate sedation with artificial intelligence: A pilot study.

Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry Aug 22, 2024
PURPOSE/OBJECTIVES: A precordial stethoscope (PS) is essential for ensuring clear breath sounds during open airway sedations. However, a traditional PS limits the ability of new users to simultaneously listen to heart and lung sounds alongside experi...
Surveys and Questionnaires Humans Monitoring, Physiologic Artificial Intelligence Respiratory Sounds Conscious Sedation Pilot Projects Anesthesia, Dental
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Automating sedation state assessments using natural language processing.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing Mar 26, 2024
INTRODUCTION: Common goals for procedural sedation are to control pain and ensure the patient is not moving to an extent that is impeding safe progress or completion of the procedure. Clinicians perform regular assessments of the adequacy of procedur...
Humans Algorithms Male Middle Aged Hypnotics and Sedatives Female Adult Prospective Studies Natural Language Processing Conscious Sedation
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Pharmacologically informed machine learning approach for identifying pathological states of unconsciousness via resting-state fMRI.

NeuroImage Oct 29, 2019
Determining the level of consciousness in patients with disorders of consciousness (DOC) remains challenging. To address this challenge, resting-state fMRI (rs-fMRI) has been widely used for detecting the local, regional, and network activity differe...
Middle Aged Functional Neuroimaging Child Support Vector Machine Adolescent Young Adult Adult Male Neural Networks, Computer Female Consciousness Disorders Humans Conscious Sedation Machine Learning Aged Wakefulness Deep Sedation Magnetic Resonance Imaging Brain Persistent Vegetative State Rest Anesthesia, General Unconsciousness
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Comparing blind spots of unsedated ultrafine, sedated, and unsedated conventional gastroscopy with and without artificial intelligence: a prospective, single-blind, 3-parallel-group, randomized, single-center trial.

Gastrointestinal endoscopy Sep 18, 2019
BACKGROUND AND AIMS: EGD is the most vital procedure for the diagnosis of upper GI lesions. We aimed to compare the performance of unsedated ultrathin transoral endoscopy (U-TOE), unsedated conventional EGD (C-EGD), and sedated C-EGD with or without ...
Pain, Procedural Endoscopy, Digestive System Conscious Sedation Single-Blind Method Adult Gastroscopy Male Prospective Studies Gastroscopes Humans Female Anxiety Artificial Intelligence Middle Aged Aged Image Processing, Computer-Assisted
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Clinical decision support system, using expert consensus-derived logic and natural language processing, decreased sedation-type order errors for patients undergoing endoscopy.

Journal of the American Medical Informatics Association : JAMIA Jan 15, 2021
OBJECTIVE: Determination of appropriate endoscopy sedation strategy is an important preprocedural consideration. To address manual workflow gaps that lead to sedation-type order errors at our institution, we designed and implemented a clinical decisi...
Deep Sedation Medication Errors Conscious Sedation Middle Aged Decision Support Systems, Clinical Natural Language Processing Ambulatory Care Hypnotics and Sedatives Adult Endoscopy Male Female Aged Humans Retrospective Studies
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