Hospital-Based Medicine

Neural Networks for Cause of Hospitalization and Final Cause of Death Extraction from Discharge Summaries.

Determining the cause of death of hospitalized patients with cardiovascular disease is of the utmost...

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 compa...

Study on intelligent syndrome differentiation neural network model of stomachache in traditional Chinese medicine based on the real world.

Stomachache is not only disease name of Traditional Chinese medicine (TCM) but also the clinical sym...

Association rule mining for the ordered placement of traditional Chinese medicine containers: An experimental study.

In traditional Chinese medicine (TCM) clinics, the pharmacists responsible for dispensing the herbal...

Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission.

BACKGROUND: Although prediction of hospital readmissions has been studied in medical patients, it ha...

Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System.

OBJECTIVES: As the performance of a conventional track and trigger system in a rapid response system...

A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision.

OBJECTIVE: Reliable longitudinal risk prediction for hospitalized patients is needed to provide qual...

Discussion on: The paradox of the robotic approach to inguinal hernia repair in the inpatient setting.

Deep learning-based quantitative visualization and measurement of extraperitoneal hematoma volumes in patients with pelvic fractures: Potential role in personalized forecasting and decision support.

INTRODUCTION: Admission computed tomography (CT) is a widely used diagnostic tool for patients with ...

Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.

Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack co...

Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations.

BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observa...

Evaluation of clinical impact of pharmacogenomics knowledge involved in CPIC guidelines on Chinese pediatric patients.

To evaluate the clinical benefits of implementing pharmacogenomics testing for Chinese pediatric pa...

Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT.

The volume of pelvic hematoma at CT has been shown to be the strongest independent predictor of majo...

Innovation technology in neurorehabilitation: introducing a hub and spoke model to avoid patient "migration" in Sicily.

PURPOSE: In the Italian National Health Service, hospital planning has been influenced by two aspect...

Using Machine Learning in Psychiatry: The Need to Establish a Framework That Nurtures Trustworthiness.

The rapid embracing of artificial intelligence in psychiatry has a flavor of being the current "wild...

Evaluating the Effect of Dexmedetomidine on Hemodynamic Status of Patients with Septic Shock Admitted to Intensive Care Unit: A Single-Blind Randomized Controlled Trial.

Septic shock, known as the most severe complication of sepsis, is a serious medical condition that c...

Laparoscopic versus Robotic Peripheral Pancreatectomy: A Systematic Review and Meta-analysis.

PURPOSE: The current systematic review and meta-analysis aimed to compare Laparoscopic Distal Pancre...

Reparación de hernias paraesofágicas gigantes asistida por robot en un hospital de cuarto nivel en Bogotá, Colombia, Clínica Shaio: serie de casos y revisión de la literatura.

BACKGROUND: Giant paraesophageal hernias have a surgical indication in case of symptoms. Since twent...

Postimplementation Evaluation of a Machine Learning-Based Deterioration Risk Alert to Enhance Sepsis Outcome Improvements.

Machine learning-based early warning systems (EWSs) can detect clinical deterioration more accuratel...

Machine Intelligence in Cardiovascular Medicine.

The computer science technology trend called artificial intelligence (AI) is not new. Both machine l...

A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presen...