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Ambulatory Care

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Word Embedding and Clustering for Patient-Centered Redesign of Appointment Scheduling in Ambulatory Care Settings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
. A key to a more efficient scheduling systems is to ensure appointments are designed to meet patient's needs and to design and simplify appointment scheduling less prone to error. Electronic Health Records (EHR) consist of valuable information about...

A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.

International journal of environmental research and public health
Late-arriving patients have become a prominent concern in several ambulatory care clinics across the globe. Accommodating them could lead to detrimental ramifications such as schedule disruption and increased waiting time for forthcoming patients, wh...

Artificial Intelligence Predictive Analytics in the Management of Outpatient MRI Appointment No-Shows.

AJR. American journal of roentgenology
Outpatient appointment no-shows are a common problem. Artificial intelligence predictive analytics can potentially facilitate targeted interventions to improve efficiency. We describe a quality improvement project that uses machine learning techniqu...

System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-Directed Clinical Evaluations During Radiation and Chemoradiation.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation or hospitalization). Machine learning (ML) may guide interventions to reduce this risk. There are limited...

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
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...

Precision Assessment of COVID-19 Phenotypes Using Large-Scale Clinic Visit Audio Recordings: Harnessing the Power of Patient Voice.

Journal of medical Internet research
COVID-19 cases are exponentially increasing worldwide; however, its clinical phenotype remains unclear. Natural language processing (NLP) and machine learning approaches may yield key methods to rapidly identify individuals at a high risk of COVID-19...

Reducing negative emotions in children using social robots: systematic review.

Archives of disease in childhood
BACKGROUND: For many children, visiting the hospital can lead to a state of increased anxiety. Social robots are being explored as a possible tool to reduce anxiety and distress in children attending a clinical or hospital environment. Social robots ...

Technology-Enabled and Artificial Intelligence Support for Pre-Visit Planning in Ambulatory Care: Findings From an Environmental Scan.

Annals of family medicine
PURPOSE: Pre-visit planning (PVP) is believed to improve effectiveness, efficiency, and experience of care, yet numerous implementation barriers exist. There are opportunities for technology-enabled and artificial intelligence (AI) support to augment...

[Clinical application of large language models : Does ChatGPT replace medical report formulation? An experience report].

Innere Medizin (Heidelberg, Germany)
Artificial intelligence (AI)-based language models, such as ChatGPT offer an enormous potential for research and medical care but also for clinical workflow optimization by making medical documentation easier and more efficient in taking over standar...