Infection Control

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.

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 patient characteristics.

[An evidence-based analysis comparing two approaches of robot-assisted laparoscopic radical prostatectomy: the standard technique and Retzius-sparing technique].

To compare the postoperative outcomes and urinary continence recovery time between standard robotic-assisted laparoscopic radical prostatectomy (RARP) and Retzius-sparing robotic-assisted laparoscopic radical prostatectomy (RsRARP). A total of 92 patients with low to intermediate-risk prostate cancer who underwent RARP (=52) and RsRARP (=40) in Sir Run Run Shaw Hospital from October, 2016 to Jan...

A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been sugge...

Design of 1-year mortality forecast at hospital admission: A machine learning approach.

Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life ...

Optimization of Genomic Classifiers for Clinical Deployment: Evaluation of Bayesian Optimization to Select Predictive Models of Acute Infection and In-Hospital Mortality.

Acute infection, if not rapidly and accurately detected, can lead to sepsis, organ failure and even death. Current detection of acute infection as wel...

Scrub typhus: An under-reported and emerging threat - hospital based study from central and eastern Uttar Pradesh, India.

BACKGROUND & OBJECTIVES: Scrub typhus is a zoonotic rickettsial disease that is transmitted by the bite of the larval stage (chiggers) of trombiculid ...

Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.

Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in h...

[Launching Robot-Assisted Laparoscopic Surgery for Rectal Cancer in Our Hospital-Short-Term Results].

Robot-assisted laparoscopic surgery(RALS)for rectal cancer has been covered by National Health Insurance in Japan since April 2018. We launched RALS i...

Patient Coded Severity and Payment Penalties Under the Hospital Readmissions Reduction Program: A Machine Learning Approach.

OBJECTIVE: The objective of this study was to examine variation in hospital responses to the Centers for Medicare and Medicaid's expansion of allowabl...

[Clinical analysis of robot-assisted laparoscopic transabdominal preperitoneal inguinal hernia repair].

To explore the clinical value of robot-assisted laparoscopic transabdominal preperitoneal (TAPP) inguinal hernia repair. We performed a retrospectiv...

[Study on the precision of the robot-assisted sacroiliac screw placement].

To evaluate the precision of the robot-assisted sacroiliac screw placement for posterior pelvis injury and the impacting factors. The clinical data ...

[Necessity of Pelvic Drain Placement after Robot-Assisted Radical Prostatectomy].

Sixty eight patients had robot-assisted radical prostatectomy (RARP) from January 2016 to April 2017 with estimated blood loss of less than 500 ml. We...

Designing an optimal inventory management model for the blood supply chain: Synthesis of reusable simulation and neural network.

Blood supply managers in the blood supply chain have always sought to create enough reserves to increase access to different blood products and reduce...

Comparison of Machine Learning Algorithms for Classifying Adverse-Event Related 30-Day Hospital Readmissions: Potential Implications for Patient Safety.

Studies in the last decade have focused on identifying patients at risk of readmission using predictive models, in an objective to decrease costs to t...

Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine l...

Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission.

BACKGROUND: Although prediction of hospital readmissions has been studied in medical patients, it has received relatively little attention in surgical...

[Research and application of orthotopic DR chest radiograph quality control system based on artificial intelligence].

With the change of medical diagnosis and treatment mode, the quality of medical image directly affects the diagnosis and treatment of the disease for ...

A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infe...

Maxwell®: An Unsupervised Learning Approach for 5P Medicine.

In the 5P medicine (Personalized, Preventive, Participative, Predictive and Pluri-expert), the general trend is to process data by displacing the bary...

Medical Equipment Replacement Prioritisation: A Comparison Between Linear and Fuzzy System Models.

In hospital management, health technology assessment techniques are being increasingly developed. This paper presents a comparison of the results obta...