Hospital-Based Medicine

ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis.

PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning.

Predicting post-stroke pneumonia using deep neural network approaches.

BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length of hospital stay and death. Therefore, the timely and accurate prediction of post-stroke pneumonia would be highly valuable in clinical practice. Previous pneumonia risk score models were often built on simple statistical methods such as logistic regression. This study aims to investigate post-stro...

Prediction of thirty-day morbidity and mortality after laparoscopic sleeve gastrectomy: data from an artificial neural network.

BACKGROUND: Multiple patient factors may convey increased risk of 30-day morbidity and mortality after laparoscopic vertical sleeve gastrectomy (LVSG)...

Artificial Intelligence for Diagnosis of Acute Coronary Syndromes: A Meta-analysis of Machine Learning Approaches.

BACKGROUND: Machine learning (ML) encompasses a wide variety of methods by which artificial intelligence learns to perform tasks when exposed to data....

Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records.

Electronic medical records (EMRs) support the development of machine learning algorithms for predicting disease incidence, patient response to treatme...

Wikidata: A large-scale collaborative ontological medical database.

Created in October 2012, Wikidata is a large-scale, human-readable, machine-readable, multilingual, multidisciplinary, centralized, editable, structur...

Deep-learning model for predicting 30-day postoperative mortality.

BACKGROUND: Postoperative mortality occurs in 1-2% of patients undergoing major inpatient surgery. The currently available prediction tools using summ...

[E-health and "Cancer outside the hospital walls", Big Data and artificial intelligence].

To heal otherwise in oncology has become an imperative of Public Health and an economic imperative in France. Patients can therefore receive live most...

Levels of Soluble Urokinase Plasminogen Activator Receptor in Pediatric Lower Respiratory Tract Infections.

Lower respiratory tract infections (LTRIs) are the most common cause of pediatric emergency department visits and are associated with significant mor...

Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection.

Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where epileptic seizure can lead to life-threatening emergencies. By...

The effect of using Gait Exercise Assist Robot (GEAR) on gait pattern in stroke patients: a cross-sectional pilot study.

: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing ...

Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests.

IMPORTANCE: Laboratory testing is an important target for high-value care initiatives, constituting the highest volume of medical procedures. Prior st...

Prediction model for the water jet falling point in fire extinguishing based on a GA-BP neural network.

Past research on the process of extinguishing a fire typically used a traditional linear water jet falling point model and the results ignored externa...

Predicting Hospital Readmission: A Joint Ensemble-Learning Model.

Hospital readmission is among the most critical issues in the healthcare system due to its high prevalence and cost. The improvement effort necessitat...

Early Esophageal Cancer: A Gastroenterologist's Disease.

Traditionally, early esophageal cancer (i.e., cancer limited to the mucosa or superficial submucosa) was managed surgically; the gastroenterologist's ...

Could deep learning in neural networks improve the QSAR models?

Assessing chemical toxicity is a multidisciplinary process, traditionally involving in vivo, in vitro and in silico tests. Currently, toxicological go...

Hospital readmissions after limited vs. extended lymph node dissection during open and robot-assisted radical prostatectomy.

PURPOSE: Differences exist concerning when and how to perform lymph node dissection (LND) during radical prostatectomy due to lack of high-grade evide...

Mapping anatomical related entities to human body parts based on wikipedia in discharge summaries.

*: Background Consisting of dictated free-text documents such as discharge summaries, medical narratives are widely used in medical natural language p...

Perioperative mortality and morbidity of outpatient versus inpatient robot-assisted radical prostatectomy: A propensity matched analysis.

OBJECTIVES: To compare the early (≤30 days) postoperative mortality and morbidity in patients who underwent robot-assisted radical prostatectomy (RARP...

Is a Drain Needed After Robotic Radical Prostatectomy With or Without Pelvic Lymph Node Dissection? Results of a Single-Center Randomized Clinical Trial.

To investigate by means of a randomized clinical trial the safety of no drain in the pelvic cavity after robot-assisted radical prostatectomy (RARP) ...