Hospital-Based Medicine

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

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[A brief history of artificial intelligence].

For more than a decade, we have witnessed an acceleration in the development and the adoption of art...

An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of in Relation to Hydrographic Conditions.

Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the...

TAPER: Time-Aware Patient EHR Representation.

Effective representation learning of electronic health records is a challenging task and is becoming...

Machine learning models to predict length of stay and discharge destination in complex head and neck surgery.

BACKGROUND: This study develops machine learning (ML) algorithms that use preoperative-only features...

Synchronous Robot-Assisted Pulmonary and Urologic Resections for Cancer.

Synchronous cancers should be first evaluated at high-volume referral oncological centers. Multidisc...

Predicting preventable hospital readmissions with causal machine learning.

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

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the stagge...

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...

Adoption of Single-Port Robotic Prostatectomy: Two Alternative Strategies.

To demonstrate two distinct methods for adopting the single-port (SP) robotic surgery system for ro...

Natural language processing with machine learning to predict outcomes after ovarian cancer surgery.

OBJECTIVE: To determine if natural language processing (NLP) with machine learning of unstructured f...

Identification of exacerbation risk in patients with liver dysfunction using machine learning algorithms.

The prediction of the liver failure (LF) and its proper diagnosis would lead to a reduction in the c...

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 ...

Clinical Predictive Models for COVID-19: Systematic Study.

BACKGROUND: COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapi...

Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?

BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascu...

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...

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