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Length of Stay

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DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning.

Scientific reports
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging a...

Defining and discriminating responders from non-responders following transurethral resection of the prostate.

Scandinavian journal of urology
BACKGROUND: Transurethral resection of the prostate (TURP) is the reference standard surgical treatment for lower urinary tract symptoms (LUTS) related to benign prostatic enlargement. The aim of this study was to investigate the response rate follow...

Predictors of in-hospital length of stay among cardiac patients: A machine learning approach.

International journal of cardiology
OBJECTIVE: The In-hospital length of stay (LOS) is expected to increase as cardiovascular diseases complexity increases and the population ages. This will affect healthcare systems especially with the current situation of decreased bed capacity and i...

Development and Validation of a Machine Learning Algorithm After Primary Total Hip Arthroplasty: Applications to Length of Stay and Payment Models.

The Journal of arthroplasty
BACKGROUND: Value-based payment programs in orthopedics, specifically primary total hip arthroplasty (THA), present opportunities to apply forecasting machine learning techniques to adjust payment models to a specific patient or population. The objec...

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...

Ensuring Fairness in Machine Learning to Advance Health Equity.

Annals of internal medicine
Machine learning is used increasingly in clinical care to improve diagnosis, treatment selection, and health system efficiency. Because machine-learning models learn from historically collected data, populations that have experienced human and struct...

Comparative effectiveness of human scope assistant versus robotic scope holder in laparoscopic resection for colorectal cancer.

Surgical endoscopy
BACKGROUND: Several types of robotic scope holders have been developed to date, but there are only some experimental reports or the results of small clinical cases. The Soloassist® system is a unique robotic scope holder with which the surgeon can co...