Hospital-Based Medicine

Infection Control

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

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In-hospital mortality and morbidity after robotic coronary artery surgery.

OBJECTIVES: The objective of this study was to assess the impact of robotic approaches on outcomes o...

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospi...

[Infection prevention check-in and infection prevention check-out to prevent nosocomial infections].

BACKGROUND: A precondition for the success of the prevention of SSI is the complete realisation of t...

Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating ...

[Development of a machine learning-based diagnostic model for T-shaped uterus using transvaginal 3D ultrasound quantitative parameters].

To develop a machine learning diagnostic model for T-shaped uterus based on quantitative parameters...

Exploring Machine Learning for Predicting Peripheral and Central Precocious Puberty Through Cross-Hospital Validation.

Precocious puberty, including Peripheral Precocious Puberty (PPP) and Central Precocious Puberty (CP...

Assessing real-life food consumption in hospital with an automatic image recognition device: A pilot study.

BACKGROUND AND AIMS: Accurate dietary intake assessment is essential for nutritional care in hospita...

Predicting prolonged length of in-hospital stay in patients with non-ST elevation myocardial infarction (NSTEMI) using artificial intelligence.

BACKGROUND: Patients presenting with non-ST elevation myocardial infarction (NSTEMI) are typically e...

Patient prioritization for pharmaceutical intervention in the hospital setting: a retrospective cross-sectional study.

OBJECTIVES: Prioritization of patients requiring pharmaceutical intervention is critical given limit...

Real-time FT-IR typing of Klebsiella pneumoniae: a flexible and rapid approach for outbreak detection and infection control.

BACKGROUND: Expansion of carbapenemase-producing Klebsiella pneumoniae (CP-Kp) is driven by within-h...

Machine learning risk-prediction model for in-hospital mortality in Takotsubo cardiomyopathy.

BACKGROUND: Takotsubo cardiomyopathy (TC) is an acute heart failure syndrome characterized by transi...

MACHINE LEARNING AND SHOCK INDICES-DERIVED SCORE FOR PREDICTING CONTRAST-INDUCED NEPHROPATHY IN ACUTE CORONARY SYNDROME PATIENTS.

Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary sy...

Stratifying Risk for Postpartum Depression at Time of Hospital Discharge.

OBJECTIVE: Postpartum depression (PPD) is a major contributor to postpartum morbidity and mortality....

Postoperative self-care ability of continuous nursing based on artificial intelligence for stroke patients with neurological injury.

According to the statistics of relevant data, stroke is a relatively common cerebrovascular disease,...

Inter-hospital transferability of AI: A case study on phase recognition in cholecystectomy.

BACKGROUND: Identifying surgical phases is a crucial component of surgical workflow analysis, facili...

Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.

BACKGROUND: Acute pancreatitis (AP) represents a critical medical condition where timely and precise...

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