Hospital-Based Medicine

Latest AI and machine learning research in hospital-based medicine for healthcare professionals.

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Ambient air pollution and cardiovascular disease rate an ANN modeling: Yazd-Central of Iran.

This study was aimed to investigate the air pollutants impact on heart patient's hospital admission ...

Single- versus multi-port robotic partial nephrectomy: a comparative analysis of perioperative outcomes and analgesic requirements.

Evidence supporting the safe use of the single-port (SP) robot for partial nephrectomy is scarce. Th...

An Audit of Robot-Assisted Minimally Invasive Surgeries in Children: Early Experience from a Tertiary Care Center in India.

Over the last decade, a significant rise in pediatric robot-assisted minimally invasive surgeries h...

A Comparison of Clinical Outcomes Between Two Different Models of Surgical Robots in Roux-en-Y Gastric Bypass.

For the past 20 years, robotic surgical systems have been used for the Roux-en-Y gastric bypass (RY...

Implementing an Individual-Centric Discharge Process across Singapore Public Hospitals.

Singapore is one of the first known countries to implement an individual-centric discharge process a...

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.

BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, ris...

The "GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork": Origins, Rationale, Organization, and Prospects.

Musculoskeletal research has been enriched in the past ten years with a great wealth of new discover...

Natural language processing for prediction of readmission in posterior lumbar fusion patients: which free-text notes have the most utility?

BACKGROUND CONTEXT: The increasing volume of free-text notes available in electronic health records ...

Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmona...

Future roles of artificial intelligence in early pain management of newborns.

The advent of increasingly sophisticated medical technology, surgical interventions, and supportive ...

Universal Physiological Representation Learning With Soft-Disentangled Rateless Autoencoders.

Human computer interaction (HCI) involves a multidisciplinary fusion of technologies, through which ...

Using the Super Learner algorithm to predict risk of 30-day readmission after bariatric surgery in the United States.

BACKGROUND: Risk prediction models that estimate patient probabilities of adverse events are commonl...

Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts.

This study aims to develop and validate prediction models for the number of all heatstroke cases, an...

Predicting Recurrence for Patients With Ischemic Cerebrovascular Events Based on Process Discovery and Transfer Learning.

The recurrence of Ischemic cerebrovascular events (ICE) often results in a high rate of mortality an...

Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics.

Disruptive innovation is an invention that disrupts an existing market and creates a new one by prov...

Symbiotic Design Application in Healthcare: Preventing Hospital Acquired Infections.

Any clinical decision support (CDS) design project integrating computational technologies with clini...

Perioperative and Oncologic Outcomes of Single-Port Multiport Robot-Assisted Radical Prostatectomy: A Meta-Analysis.

Although single-port robot-assisted radical prostatectomy (SP-RARP) is considered a safe and feasib...

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