Hospital-Based Medicine

Staging Paro: The care of making robot(s) care.

Paro, a baby seal robot, is arguably the best-known care robot worldwide. Its clinical effects on people with special needs have been studied for more than twenty years by multidisciplinary teams. However, there are very few studies of Paro 'in the wild', inserted in the routines and pressures of a care home, which is supposed to be Paro's natural environment. Based on fieldwork in a French public...

Laparoscopic simple prostatectomy versus robot-assisted simple prostatectomy for large benign prostatic hyperplasia: a systematic review and meta-analysis of comparative trials.

Laparoscopic simple prostatectomy (LSP) and robot-assisted simple prostatectomy (RASP) are important approaches for large benign prostatic hyperplasia (BPH), though it is still unclear which is superior. This study aimed to perform a pooled analysis to compare the safety and efficacy profiles of LSP and RASP. We systematically searched the databases of Science, PubMed, Embase, Web of Science, and ...

Comparison of Perioperative Outcomes Between Retroperitoneal Single-Port and Multiport Robot-Assisted Partial Nephrectomies.

To report early institutional experience with the single-port robotic platform and compare perioperative outcomes between single-port robot-assisted ...

Predicting mortality in the very old: a machine learning analysis on claims data.

Machine learning (ML) may be used to predict mortality. We used claims data from one large German insurer to develop and test differently complex ML p...

Pivotal challenges in artificial intelligence and machine learning applications for neonatal care.

Clinical decision support systems (CDSS) that are developed based on artificial intelligence and machine learning (AI/ML) approaches carry transformat...

Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method.

It is of great significance to explore the characteristic factors of postoperative nursing safety events in patients with otolaryngology surgery and t...

Delirium screening in an acute care setting with a machine learning classifier based on routinely collected nursing data: A model development study.

Delirium screening in acute care settings is a resource intensive process with frequent deviations from screening protocols. A predictive model relyin...

Developing EMR-based algorithms to Identify hospital adverse events for health system performance evaluation and improvement: Study protocol.

BACKGROUND: Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative da...

De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.

Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value to medical researchers. However, this information i...

Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI).

OBJECTIVES: Artificial intelligence (AI) is seen as a major disrupting force in the future healthcare system. However, the assessment of the value of ...

Robot-Assisted Partial Nephrectomy with a New Robotic Surgical System: Feasibility and Perioperative Outcomes.

The aim of this study was to evaluate the feasibility and safety of a novel robotic system (KD-SR-01) for partial nephrectomy. Seventeen patients wi...

Robot-Assisted Versus Laparoscopic Approach for Splenectomy in Children: Systematic Review and Meta-Analysis.

To compare the outcomes of pediatric splenectomies for hematologic diseases performed by robot-assisted laparoscopic surgery (RALS) and laparoscopic ...

Minimally Invasive Surgery in the United States, 2022: Understanding Its Value Using New Datasets.

INTRODUCTION: While minimally invasive surgery (MIS) has transformed the treatment landscape of surgical care, its utilization is not well understood....

Prescreening and Triage of COVID-19 Patients Through Chest X-Ray Images Using Deep Learning Model.

Deep learning models deliver a fast diagnosis during triage prescreening for COVID-19 patients, reducing waiting time for hospital admission during he...

Comparison of physician and artificial intelligence-based symptom checker diagnostic accuracy.

Symptom checkers are increasingly used to assess new symptoms and navigate the health care system. The aim of this study was to compare the accuracy o...

Length of Stay Prediction Model of Indoor Patients Based on Light Gradient Boosting Machine.

The influx of hospital patients has become common in recent years. Hospital management departments need to redeploy healthcare resources to meet the m...

A Comprehensive Quantitative and Biological Neural Network Optimization Model of Sports Industry Structure Based on Knowledge Mapping.

In this paper, a comprehensive quantitative and biological neural network optimization model of sports industry structure is thoroughly studied and an...

Occupational health and safety risk assessment using a fuzzy multi-criteria approach in a hospital in Chennai, India.

Hospitals provide direct and indirect employment benefits to medical professionals. Accidents in hospitals often lead to disastrous consequences such...

An automated deep learning method and novel cardiac index to detect canine cardiomegaly from simple radiography.

Since most of degenerative canine heart diseases accompany cardiomegaly, early detection of cardiac enlargement is main priority healthcare issue for ...

Insulator Leakage Current Prediction Using Hybrid of Particle Swarm Optimization and Gene Algorithm-Based Neural Network and Surface Spark Discharge Data.

This study proposes a new superior hybrid algorithm, which is the particle swarm optimization (PSO) and gene algorithm (GA)-based neural network to pr...