AIMC Topic: Outpatients

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Automated Safety Plan Scoring in Outpatient Mental Health Settings Using Large Language Models: Exploratory Study.

JMIR mental health
BACKGROUND: The safety planning intervention (SPI) is a suicide prevention intervention that results in a written plan to help patients reduce suicide risk. High-quality safety plans-that is, those that are the most complete, personalized, and specif...

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...

Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study.

JMIR medical informatics
BACKGROUND: The integration of artificial intelligence (AI) into clinical workflows holds promise for enhancing outpatient decision-making and patient education. ChatGPT, a large language model developed by OpenAI, has gained attention for its potent...

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...

Development and validation of a hypoxemia prediction model in middle-aged and elderly outpatients undergoing painless gastroscopy.

Scientific reports
Hypoxemia is a common complication associated with anesthesia in painless gastroscopy. With the aging of the social population, the number of cases of hypoxemia among middle-aged and elderly patients is increasing. However, tools for predicting hypox...

Splenic and portal venous flow associated with frailty and sarcopenia in older outpatients with cardiovascular disease.

BMC geriatrics
BACKGROUND: Older patients with cardiovascular disease often experience frailty and sarcopenia. We evaluated whether a reduced blood flow in the splenic and portal vein is associated with frailty and sarcopenia in older patients with cardiovascular d...

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...

Improving diagnosis-based quality measures: an application of machine learning to the prediction of substance use disorder among outpatients.

BMJ open quality
OBJECTIVE: Substance use disorder (SUD) is clinically under-detected and under-documented. We built and validated machine learning (ML) models to estimate SUD prevalence from electronic health record (EHR) data and to assess variation in facility-lev...

Objective approach to diagnosing attention deficit hyperactivity disorder by using pixel subtraction and machine learning classification of outpatient consultation videos.

Journal of neurodevelopmental disorders
BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common childhood neurodevelopmental disorder, affecting between 5% and 7% of school-age children. ADHD is typically characterized by persistent patterns of inattention or hyperactivity-...