Hospital-Based Medicine

Robot-assisted versus laparoscopic living donor nephrectomy: superior outcomes after completion of the learning curve.

The use of robots in donor nephrectomy has increased in recent years. However, whether robot-assisted methods have better outcomes than traditional laparoscopic methods and how surgical experience influences these outcomes remains unclear. This meta-analysis compares the outcomes of robot-assisted donor nephrectomy (RADN) with those of laparoscopic donor nephrectomy (LDN) and to investigate the ef...

An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration.

Emergency department (ED) triage scale determines the priority of patient care and foretells the prognosis. However, the information retrieved from the initial assessment is limited, hindering the risk identification accuracy of triage. Therefore, we sought to develop a 'dynamic' triage system as secondary screening, using artificial intelligence (AI) techniques to integrate information from initi...

Prediction of Postoperative Creatinine Levels by Artificial Intelligence after Partial Nephrectomy.

: Multiple factors are associated with postoperative functional outcomes, such as acute kidney injury (AKI), following partial nephrectomy (PN). The p...

ChatGPT Helped Me Write This Talk Title, but Can It Read an Echocardiogram?

While multidisciplinary collaboration in echocardiography is not new, machine learning has the potential to further improve it. In this transcript of ...

Improving Diagnostics with Deep Forest Applied to Electronic Health Records.

An electronic health record (EHR) is a vital high-dimensional part of medical concepts. Discovering implicit correlations in the information of this d...

Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.

Artificial intelligence (AI) promises to revolutionize many fields, but its clinical implementation in cardiovascular imaging is still rare despite in...

Recent advances in wearable sensors and data analytics for continuous monitoring and analysis of biomarkers and symptoms related to COVID-19.

The COVID-19 pandemic has changed the lives of many people around the world. Based on the available data and published reports, most people diagnosed ...

Machine learning methods for anomaly classification in wastewater treatment plants.

Modern wastewater treatment plants base their biological processes on advanced control systems which ensure compliance with discharge limits and minim...

Establishing a Health CASCADE-Curated Open-Access Database to Consolidate Knowledge About Co-Creation: Novel Artificial Intelligence-Assisted Methodology Based on Systematic Reviews.

BACKGROUND: Co-creation is an approach that aims to democratize research and bridge the gap between research and practice, but the potential fragmenta...

Establishment of a successful robotic pediatric general surgery practice.

Robotic-assisted surgery (RAS) has a variety of theoretical advantages, including tremor filtration, optimal visualization, and improvement of surgeon...

Prediction of oxygen supplementation by a deep-learning model integrating clinical parameters and chest CT images in COVID-19.

PURPOSE: As of March 2023, the number of patients with COVID-19 worldwide is declining, but the early diagnosis of patients requiring inpatient treatm...

Machine learning to predict curative multidisciplinary team treatment decisions in oesophageal cancer.

BACKGROUND: Rising workflow pressures within the oesophageal cancer (OC) multidisciplinary team (MDT) can lead to variability in decision-making, and ...

Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data.

Since the beginning of the COVID-19 pandemic, new and non-invasive digital technologies such as artificial intelligence (AI) had been introduced for m...

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.

BACKGROUND: Unintentional injury is the leading cause of death in young children. Emergency department (ED) diagnoses are a useful source of informati...

Early perioperative outcomes of single-port compared to multi-port robot-assisted laparoscopic partial nephrectomy.

Single-port (SP) robot-assisted laparoscopic partial nephrectomy (RAPN) is a promising new technique. The aim of this study was to compare surgical an...

Home-based upper limb stroke rehabilitation mechatronics: challenges and opportunities.

Interest in home-based stroke rehabilitation mechatronics, which includes both robots and sensor mechanisms, has increased over the past 12 years. The...

Open versus robot-assisted partial nephrectomy for highly complex renal masses: a meta-analysis of perioperitive and functional outcomes.

Robot-assisted partial nephrectomy (RAPN) is increasingly being used for the complex surgical management of renal masses. The comparison of RAPN with ...

Identifying inpatient mortality in MarketScan claims data using machine learning.

PURPOSE: Inpatient mortality is an important variable in epidemiology studies using claims data. In 2016, MarketScan data began obscuring specific hos...

Management for Benign Ureteral Stricture: Comparison of Robot-Assisted Laparoscopy, Conventional Laparoscopy, and Balloon Dilation.

Robot-assisted laparoscopy (RALP), conventional laparoscopy (LP), and balloon dilation (BD) have all been identified as common treatments for benign ...

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed ...