Hospital-Based Medicine

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

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Combination Therapy of Chloramphenicol and Daptomycin for the Treatment of Infective Endocarditis Secondary to Multidrug Resistant .

A 38-years-old female with an aortic valve replacement presented to an outside hospital (OSH) with f...

Predicting self-intercepted medication ordering errors using machine learning.

Current approaches to understanding medication ordering errors rely on relatively small manually cap...

AI in drug development: a multidisciplinary perspective.

The introduction of a new drug to the commercial market follows a complex and long process that typi...

Using machine learning to predict severe hypoglycaemia in hospital.

AIM: To predict the risk of hypoglycaemia using machine-learning techniques in hospitalized patients...

Prediction Model Using Machine Learning for Mortality in Patients with Heart Failure.

Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US popul...

Robot assisted minimally invasive esophagectomy: safety, perioperative morbidity and short-term oncological outcome-a single institution experience.

Robot assisted minimally invasive esophagectomy (RAMIE) has evolved over the past decade to become p...

A machine learning based exploration of COVID-19 mortality risk.

Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring eff...

Comparison of deep learning, radiomics and subjective assessment of chest CT findings in SARS-CoV-2 pneumonia.

PURPOSE: Comparison of deep learning algorithm, radiomics and subjective assessment of chest CT for ...

Predictive modelling of piezometric head and seepage discharge in earth dam using soft computational models.

Predictions of pore pressure and seepage discharge are the most important parameters in the design o...

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

Identification of those at greatest risk of death due to the substantial threat of COVID-19 can bene...

A classification approach to estimating human circadian phase under circadian alignment from actigraphy and photometry data.

The time of dim light melatonin onset (DLMO) is the gold standard for circadian phase assessment in ...

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach.

The efficient and reliable monitoring of the flow of water in open channels provides useful informat...

Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction.

Machine learning (ML) has been suggested to improve the performance of prediction models. Neverthele...

A Multifunctional Smart Meter Using ANN-PSO Flux Estimation and Harmonic Active Compensation with Fuzzy Voltage Regulation.

This paper aims to present the analysis and development of a complete electronic smart meter that is...

Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).

In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortali...

A Pragmatic Machine Learning Model To Predict Carbapenem Resistance.

Infection caused by carbapenem-resistant (CR) organisms is a rising problem in the United States. Wh...

Severe intraoperative bleeding predicts the risk of perioperative blood transfusion after robot-assisted radical prostatectomy.

To evaluate potential factors associated with the risk of perioperative blood transfusion (PBT) with...

The future of basic science in orthopaedics and traumatology: Cassandra or Prometheus?

Orthopaedic and trauma research is a gateway to better health and mobility, reflecting the ever-incr...

Commentary: When will the robots come marching in?

Minimally invasive techniques for coronary artery bypass grafting (CABG), specifically robotic-assis...

Machine ​learning algorithms for claims data-based prediction of in-hospital mortality in patients with heart failure.

AIMS: Models predicting mortality in heart failure (HF) patients are often limited with regard to pe...

How do machine learning algorithms perform in predicting hospital choices? evidence from changing environments.

Researchers have found that machine learning methods are typically better at prediction than econome...

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