Hospital-Based Medicine

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

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Relationship between Artificial Intelligence-Based General Anesthetics and Postoperative Cognitive Dysfunction.

Postoperative cognitive dysfunction (POCD) refers to the complications of the central nervous system...

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and ...

Machine learning-based analysis of alveolar and vascular injury in SARS-CoV-2 acute respiratory failure.

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pneumopathy is characterized by a compl...

[Robot-assisted Living Donor Nephrectomy - Technical Aspects and Initial Evidence].

Minimally invasive donor nephrectomy has become the standard procedure in most transplant centres ov...

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT.

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (C...

Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview.

Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunat...

Robotic-assisted radical prostatectomy following colo-rectal surgery: a user's guide.

To assess the feasibility and operative outcomes of RARP following colo-rectal surgery. A prospectiv...

Anaesthesia management during paediatric robotic surgery: preliminary results from a single centre multidisciplinary experience.

INTRODUCTION: Paediatric robotic surgery is gaining popularity across multiple disciplines and offer...

Using deep learning and natural language processing models to detect child physical abuse.

BACKGROUND: The recognition of child physical abuse can be challenging and often requires a multidis...

Predicting Readmission After Anterior, Posterior, and Posterior Interbody Lumbar Spinal Fusion: A Neural Network Machine Learning Approach.

BACKGROUND: Readmission after spine surgery is costly and a relatively common occurrence. Previous r...

Mixed-data deep learning in repeated predictions of general medicine length of stay: a derivation study.

The accurate prediction of likely discharges and estimates of length of stay (LOS) aid in effective ...

AI support for ethical decision-making around resuscitation: proceed with care.

Artificial intelligence (AI) systems are increasingly being used in healthcare, thanks to the high l...

The effect of diabetes on major robotic hepatectomy.

Studies regarding the influence of diabetes on perioperative outcomes after major hepatectomy are co...

Machine Learning Compared With Conventional Statistical Models for Predicting Myocardial Infarction Readmission and Mortality: A Systematic Review.

BACKGROUND: Machine learning (ML) methods are increasingly used in addition to conventional statisti...

Individualized prediction of COVID-19 adverse outcomes with MLHO.

The COVID-19 pandemic has devastated the world with health and economic wreckage. Precise estimates ...

Should Peritoneal Re-Approximation Be Performed After Transperitoneal Robot-Assisted Radical Prostatectomy?

The aim of the study is to examine the effect of peritoneal re-approximation or non-approximation o...

Semi-automated tracking of pain in critical care patients using artificial intelligence: a retrospective observational study.

Monitoring the pain intensity in critically ill patients is crucial because intense pain can cause a...

Deep Learning for Accelerometric Data Assessment and Ataxic Gait Monitoring.

Ataxic gait monitoring and assessment of neurological disorders belong to important multidisciplinar...

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