PREOPERATIVE PREDICTION AND RISK FACTOR IDENTIFICATION OF HOSPITAL LENGTH OF STAY FOR TOTAL JOINT ARTHROPLASTY PATIENTS USING MACHINE LEARNING

Preoperative Prediction and Risk Factor Identification of Hospital Length of Stay for Total Joint Arthroplasty Patients Using Machine Learning

Background: The aim of this study was to improve understanding of hospital length of stay (LOS) in patients undergoing total joint arthroplasty (TJA) in a high-efficiency, hospital-based pathway.Methods: We retrospectively reviewed 1401 consecutive primary and revision TJA patients across 67 patient and preoperative care characteristics from 2016 t

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Analysis and countermeasures for product pipeline internal corrosion based on first-run in-line inspection data

In order to monitor, prevent and control the corrosion in in-service product pipelines, the value of the first-run inline inspection data was further mined, and the analysis idea was proposed in such a way that, the internal corrosion sensitive area should be semi-quantitatively located through differential Swim Parts analysis of the dispersion of

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A fuzzy logic based approach for prediction of basal cell carcinoma and squamous cell carcinoma among the data of skin cancer

INTRODUCTION: Both basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) is a type of skinmalignancy which are deadly in nature.Although both can cause a serious setback for the human body, SCC ismost dangerous as per human life is concerned.OBJECTIVES: It is necessary to spot out the cases of SCC and BCC among various data of skin cancer.In

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