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Outpatients

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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...

Predictors for improvement in personality functioning during outpatient psychotherapy: A machine learning approach within a psychodynamic psychotherapy sample.

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Since its introduction in the diagnostic manuals DSM-5 and ICD-11, the construct of personality functioning has gained increasing attention. However, it remains unclear which factors might predict improvement in personality functioning.

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-...

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...

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...

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...

Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.

Journal of neuroengineering and rehabilitation
BACKGROUND: Knee osteoarthritis (KOA) is a prevalent chronic disease worldwide, and traditional treatment methods lack personalized adjustment for individual patient differences and cannot meet the needs of personalized treatment.

Predicting hospital outpatient volume using XGBoost: a machine learning approach.

Scientific reports
Hospital outpatient volume is influenced by a variety of factors, including environmental conditions and healthcare resource availability. Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allo...