AIMC Topic: Length of Stay
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Machine learning to predict passenger mortality and hospital length of stay following motor vehicle collision.
Neurosurgical focus
Apr 1, 2022
OBJECTIVE: Motor vehicle collisions (MVCs) account for 1.35 million deaths and cost $518 billion US dollars each year worldwide, disproportionately affecting young patients and low-income nations. The ability to successfully anticipate clinical outco...
Length of Stay Prediction in Neurosurgery with Russian GPT-3 Language Model Compared to Human Expectations.
Studies in health technology and informatics
Jan 14, 2022
Patients, relatives, doctors, and healthcare providers anticipate the evidence-based length of stay (LOS) prediction in neurosurgery. This study aimed to assess the quality of LOS prediction with the GPT3 language model upon the narrative medical rec...
Artificial intelligence guided predicting the length of hospital-stay in a neurosurgical hospital based on the text data of electronic medical records.
Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko
Jan 1, 2022
BACKGROUND: Rational use of internal resources of hospitals including bed fund turnover is important objective in high-tech medicine. Machine learning technologies can improve neurosurgical care and contribute to patient-oriented approach.
[Comparison of robot-assisted and conventional endoscopic surgeries in the Russian Federation. (A systematic review and meta-analysis)].
Khirurgiia
Jan 1, 2022
OBJECTIVE: Comparative assessment of immediate and long-term results of robot-assisted and conventional endoscopic technologies in the Russian Federation.
Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).
Critical care medicine
Jan 1, 2022
OBJECTIVES: Delirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a to...
Comparison of Perioperative Outcomes for Radical Nephrectomy Based on Surgical Approach for Masses Greater Than 10 cm.
Journal of endourology
Dec 1, 2021
Robot-assisted radical nephrectomy (RRN) is increasingly utilized as an alternative to laparoscopic radical nephrectomy (LRN), but there are concerns over costs and objective benefit. In the setting of very large renal masses (>10 cm), comparison be...
[Artificial Intelligence in internal medicine : development of a model predicting length of stay for non-elective admissions].
Revue medicale suisse
Nov 24, 2021
Efficient management of hospitalized patients requires carefully planning each stay by taking into account patients' pathologies and hospital constraints. Therefore, the ability to accurately estimate length of stays allows for better interprofession...
The Cost of Robot-assisted Total Hip Arthroplasty: Comparing Safety and Hospital Charges to Conventional Total Hip Arthroplasty.
The Journal of the American Academy of Orthopaedic Surgeons
Jul 15, 2021
INTRODUCTION: Utilization of robotic assistance is increasing for total hip arthroplasty (THA). However, few studies have directly examined the efficacy of this technique at reducing complications. This research aims to compare the rates of periopera...
Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patien...
Gynecological Surgery and Machine Learning: Complications and Length of Stay Prediction.
Studies in health technology and informatics
May 27, 2021
In this study we are developing predictive models for a length of stay after a gynecological surgery, complications and the length of the surgery using machine learning methods. The study was performed with the data of patients with the diseases of t...
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