Hospital-Based Medicine

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

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Deep learning for predicting in-hospital mortality among heart disease patients based on echocardiography.

BACKGROUND: Heart disease (HD) is the leading cause of global death; there are several mortality pre...

Robot-assisted intravertebral augmentation corrects local kyphosis more effectively than a conventional fluoroscopy-guided technique.

OBJECTIVEIntravertebral augmentation (IVA) is a reliable minimally invasive technique for treating M...

Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study.

BACKGROUND: Resuscitated cardiac arrest is associated with high mortality; however, the ability to e...

A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospita...

Hyponatremia Presenting with Recurrent Mania.

Primary psychogenic polydipsia (PPD) is a chronic, relapsing condition in which there is a disturban...

The feasibility of fingerstick blood collection for point-of-care HIV-1 viral load monitoring in rural Zambia.

Viral load monitoring for HIV treatment is recommended but not feasible in many settings. A point-of...

The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission predictio...

A nurse-driven method for developing artificial intelligence in "smart" homes for aging-in-place.

OBJECTIVES: To offer practical guidance to nurse investigators interested in multidisciplinary resea...

A combined modelling of fuzzy logic and Time-Driven Activity-based Costing (TDABC) for hospital services costing under uncertainty.

Hospital traditional cost accounting systems have inherent limitations that restrict their usefulnes...

Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, vali...

Natural language generation for electronic health records.

One broad goal of biomedical informatics is to generate fully-synthetic, faithfully representative e...

Vitamin D in the ICU: More sun for critically ill adult patients?

Critical illness in patients is characterized by systemic inflammation and oxidative stress. Vitamin...

Multi-perspective predictive modeling for acute kidney injury in general hospital populations using electronic medical records.

OBJECTIVES: Acute kidney injury (AKI) in hospitalized patients puts them at much higher risk for dev...

Optimal intensive care outcome prediction over time using machine learning.

BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the inte...

A conceptual framework for clinicians working with artificial intelligence and health-assistive Smart Homes.

The Smart Home designed to extend older adults independence is emerging as a clinical solution to th...

Analysing repeated hospital readmissions using data mining techniques.

Few studies have examined how to identify future readmission of patients with a large number of repe...

Detection of Surgical Site Infection Utilizing Automated Feature Generation in Clinical Notes.

Postsurgical complications (PSCs) are known as a deviation from the normal postsurgical course and c...

Social robots to support children's well-being under medical treatment: A systematic state-of-the-art review.

Hospitalization is a stressful experience for children. Socially assistive robots (SARs), designed t...

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