AIMC Topic: Ambulatory Care

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Mixed-methods evaluation of how a predictive model pilot intervention addresses patient non-attendance at outpatient services in an NHS Foundation Trust in England.

BMJ open
BACKGROUND: There is interest in using predictive models to address non-attendance of healthcare appointments without prior notification. Although several National Health Service (NHS) hospital trusts have piloted predictive models for non-attendance...

Evaluating Locally Run Large Language Models (Gemma 2, Mistral Nemo, and Llama 3) for Outpatient Otorhinolaryngology Care: Retrospective Study.

JMIR formative research
BACKGROUND: Large language models (LLMs) have great potential to improve and make the work of clinicians more efficient. Previous studies have mainly focused on web-based services, such as ChatGPT, often with simulated cases. For the processing of pe...

Differential Diagnosis Assessment in Ambulatory Care With a Digital Health History Device: Pseudorandomized Study.

JMIR formative research
BACKGROUND: Digital health history devices represent a promising wave of digital tools with the potential to enhance the quality and efficiency of medical consultations. They achieve this by providing physicians with standardized, high-quality patien...

Clinical feasibility of AI Doctors: Evaluating the replacement potential of large language models in outpatient settings for central nervous system tumors.

International journal of medical informatics
BACKGROUND AND OBJECTIVES: The treatment of central nervous system (CNS) tumors is complex and resource-intensive, with higher mortality in underserved regions. Large language models (LLMs) show promise in medical support, but their real-world perfor...

Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.

BMC public health
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...

The advance of artificial intelligence in outpatient urology: current applications and future directions.

Current opinion in urology
PURPOSE OF REVIEW: Prudent integration of artificial intelligence (AI) into outpatient urology has already begun to revolutionize clinical workflows, improve administrative efficiency, and automate mundane and laborious tasks in the clinic setting.

Non-Face-to-Face Services in Neurologic Care.

Seminars in neurology
Neurologists in ambulatory settings struggle with low appointment availability and increased work related to patient care outside of clinic visits. Neurologists can better meet these demands using asynchronous or non-face-to-face care options. Specif...

Using Machine Learning to Fight Child Acute Malnutrition and Predict Weight Gain During Outpatient Treatment with a Simplified Combined Protocol.

Nutrients
BACKGROUND/OBJECTIVES: Child acute malnutrition is a global public health problem, affecting 45 million children under 5 years of age. The World Health Organization recommends monitoring weight gain weekly as an indicator of the correct treatment. Ho...

Development of Automated Triggers in Ambulatory Settings in Brazil: Protocol for a Machine Learning-Based Design Thinking Study.

JMIR research protocols
BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods e...