Hospital-Based Medicine

Infection Control

Latest AI and machine learning research in infection control for healthcare professionals.

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Perspectives of Child Life Specialists After Many Years of Working With a Humanoid Robot in a Pediatric Hospital: Narrative Design.

BACKGROUND: Child life specialists (CLSs) play an important role in supporting patients and their fa...

Closing the Digital Health Evidence Gap: Development of a Predictive Score to Maximize Patient Outcomes.

Clinical studies of telemedicine (TM) programs for chronic illness have demonstrated mixed results ...

Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve o...

Comparing machine learning with case-control models to identify confirmed dengue cases.

In recent decades, the global incidence of dengue has increased. Affected countries have responded w...

The validity of Dutch health claims data for identifying patients with chronic kidney disease: a hospital-based study in the Netherlands.

BACKGROUND: Health claims data may be an efficient and easily accessible source to study chronic kid...

Safety and efficacy of robot-assisted versus open pancreaticoduodenectomy: a meta-analysis of multiple worldwide centers.

The objective of the study is to compare the safety and efficacy of robot-assisted pancreaticoduoden...

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography.

Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVI...

Predicting preventable hospital readmissions with causal machine learning.

OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital re...

Assessment of User Needs for Telemedicine Robots in a Developing Nation Hospital Setting.

This study aimed to investigate the needs of medical users of telemedicine robots to encourage inte...

A Novel Use of Artificial Intelligence to Examine Diversity and Hospital Performance.

BACKGROUND: The US population is becoming more racially and ethnically diverse. Research suggests th...

Effect of Obesity on Clinical Outcomes of Patients Treated With Cefepime.

As the prevalence of obesity climbs, dosing of antimicrobials, particularly cephalosporins, is beco...

The implementation of a rapid sample preparation method for the detection of SARS-CoV-2 in a diagnostic laboratory in South Africa.

The SARS-CoV-2 pandemic has resulted in shortages of both critical reagents for nucleic acid purific...

Predicting defibrillation success in out-of-hospital cardiac arrested patients: Moving beyond feature design.

OBJECTIVE: Optimizing timing of defibrillation by evaluating the likelihood of a successful outcome ...

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.

BACKGROUND: Early and accurate identification of sepsis patients with high risk of in-hospital death...

How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data.

OBJECTIVES: Hospital readmission is a main cost driver for healthcare systems, but existing works of...

Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.

BACKGROUND: Hospital readmissions are a key quality metric, which has been tied to reimbursement. On...

Artificial Intelligence-Driven Oncology Clinical Decision Support System for Multidisciplinary Teams.

Watson for Oncology (WfO) is a clinical decision support system driven by artificial intelligence. I...

Predicting In-Hospital Mortality at Admission to the Medical Ward: A Big-Data Machine Learning Model.

BACKGROUND: General medical wards admit high-risk patients. Artificial intelligence algorithms can u...

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