AIMC Topic: Outpatients
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Predicting inpatient stay lasting 2 midnights or longer after robotic surgery for endometrial cancer.
Journal of minimally invasive gynecology
Jan 5, 2015
OBJECTIVE: To estimate the rate of inpatient stay and the factors predicting inpatient status after robotic surgery for endometrial cancer following the change in the Medicare definition of "inpatient" to include hospitalization spanning 2 midnights.
The use of natural language processing of infusion notes to identify outpatient infusions.
Pharmacoepidemiology and drug safety
Nov 17, 2014
PURPOSE: Outpatient infusions are commonly missing in Veterans Health Affairs (VHA) pharmacy dispensing data sets. Currently, Healthcare Common Procedure Coding System (HCPCS) codes are used to identify outpatient infusions, but concerns exist if the...
Generating Outpatient Progress Notes: A Comparison of Individualized and Generalized Models.
Studies in health technology and informatics
Aug 7, 2025
The increasing documentation workload in medical practice, particularly for clinical notes, has driven the development of AI-driven solutions. This study introduces an AI Doctor Assistant (DA) that generates drafts of outpatient progress notes. The D...
Predicting hospital outpatient volume using XGBoost: a machine learning approach.
Scientific reports
May 16, 2025
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...
Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.
Journal of neuroengineering and rehabilitation
May 8, 2025
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.
Machine learning for adverse event prediction in outpatient parenteral antimicrobial therapy: a scoping review.
The Journal of antimicrobial chemotherapy
Dec 2, 2024
OBJECTIVE: This study aimed to conduct a scoping review of machine learning (ML) techniques in outpatient parenteral antimicrobial therapy (OPAT) for predicting adverse outcomes and to evaluate their validation, implementation and potential barriers ...
Using Natural Language Processing to Extract and Classify Symptoms Among Patients with Thyroid Dysfunction.
Studies in health technology and informatics
Jan 25, 2024
In the United States, more than 12% of the population will experience thyroid dysfunction. Patient symptoms often reported with thyroid dysfunction include fatigue and weight change. However, little is understood about the relationship between these ...
Outpatient Robotic surgery: Considerations for the Anesthesiologist.
Advances in anesthesia
Dec 1, 2022
A shortage of inpatient beds and nurses during the coronavirus disease 2019 pandemic has lent priority to safe same-day discharge after surgery. The minimally invasive nature of robotic surgery has allowed an increasing number of procedures to be don...
Advancing care for acute gastrointestinal bleeding using artificial intelligence.
Journal of gastroenterology and hepatology
Feb 1, 2021
The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision making. Machine learning algorithms have shown promise in outperforming existing clinical risk score...
Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer.
JAMA oncology
Nov 1, 2020
IMPORTANCE: Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care planning. However, no ML mortality risk prediction algorithm has been prospectively validated in oncol...
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