Hospital-Based Medicine

Distinct clinical clusters of paediatric patients with status epilepticus: Retrospective cohort study.

AIM: To characterize the clinical features, management, and outcomes of paediatric patients with status epilepticus, and to explore whether distinct clinical subgroups can be identified from clinical descriptions. METHOD: This was an exploratory retrospective single-centre cohort study of paediatric status epilepticus admissions to Switzerland's largest tertiary-level paediatric hospital. We analy...

[Artificial intelligence in surgical disciplines: Clinical application, advantages, and potential-a Delphi expert consensus].

BACKGROUND: Artificial intelligence (AI) in surgical disciplines has the potential to support all areas of patient care, with the goal of improving treatment quality and patient safety. A group of multidisciplinary experts discussed the current situation as well as steps required to successfully integrate AI into surgical disciplines in the context of a consensus conference at the second Digital H...

Machine Learning Algorithms to Predict Venous Thromboembolism in Patients With Sepsis in the Intensive Care Unit: Multicenter Retrospective Study.

BACKGROUND: Venous thromboembolism (VTE) is a common and severe complication in intensive care unit (ICU) patients with sepsis. Conventional risk stra...

Early prediction of colonization by carbapenemase-producing enterobacterales at ICU admission using machine learning.

Colonization by carbapenemase-producing Enterobacterales (CPE) on admission to an intensive care unit (ICU) poses a serious threat to infection contro...

AI-enabled forecasting of prehospital transfusion needs in patients with trauma: a multinational, registry-based, retrospective, machine learning development and validation study.

BACKGROUND: Trauma is a major global cause of morbidity and mortality, with haemorrhage representing a leading preventable cause of early death. Timel...

Collaborative and Cooperative Hospital "In-House" Medical Device Development and Implementation in the AI Age: The European Responsible AI Development (EURAID) Framework Compatible With European Values.

The last years have seen an acceleration in the development and uptake of artificial intelligence (AI) systems by "early adopter" hospitals, caught be...

Artificial Intelligence in Plastic Surgery: Current Status, Limitations, and Future Directions.

Artificial intelligence (AI) has become pervasive in and beyond plastic surgery. Myriad applications exist, and patients and plastic surgeons are incr...

Detection of Antithrombotic-Related Bleeding in Older Inpatients: Multicenter Retrospective Study Using Structured and Unstructured Electronic Health Record Data.

BACKGROUND: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrom...

A comparative evaluation of time-series models for forecasting inpatient deaths and discharges against medical advice.

Forecasting inpatient mortality (IM) and discharges against medical advice (DAMA) provides essential insights for healthcare quality monitoring and ho...

Machine learning for identifying risk factors of nosocomial infection in cancer patients with immune checkpoint inhibitor-related pneumonia.

Multiple epileptiform waves detection algorithm based on improved VMD and multidimensional feature fusion.

BACKGROUND: Spikes, ripples, and ripples on spikes (RonS) during non-rapid eye movement (NREM) sleep are all important biomarkers associated with epil...

Nurses' attitudes toward artificial intelligence applications and their clinical decision-making competence: A cross-sectional study.

BACKGROUND: The increasing integration of artificial intelligence (AI) into healthcare has generated interest in its potential role within nursing pra...

Predicting Return Home After Moderate-to-Severe Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: Days alive and at home (DAH) is a validated outcome measure that captures health care transitions between time spent at hom...

Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER) in the UK: a cluster-randomised controlled implementation trial.

BACKGROUND: Early detection of cardiovascular disease is a global public health priority. Artificial intelligence (AI)-enabled stethoscopes offer robu...

Digital hypertension in 2024-2025: emerging evidence and future directions.

Recent advances in digital technology are remarkable, and they are driving profound transformations in healthcare and medical research. Within this co...

Seizure forecasting with multiple timescales and features.

OBJECTIVE: Forecasting epileptic seizures is a difficult task. Studies of seizure prediction have investigated many different EEG features, but none o...

Engineering Immune Cell to Counteract Aging and Aging-Associated Diseases.

Aging and age-related diseases are a major public health concern, driving interest in anti-aging research. While small molecules and natural compounds...

In-hospital outcomes of intravascular lithotripsy compared to rotational atherectomy and cutting/scoring balloon angioplasty.

BACKGROUND: Intravascular lithotripsy (IVL) emerged for the treatment of coronary artery calcification with encouraging safety and effectiveness rates...

Early prediction of pressure injury risk in hospitalized patients using supervised machine learning models based on nursing records.

This study aimed to employ supervised models for predicting pressure injuries in hospitalized patients using data collected within the first eight hou...

Interdisciplinary expertise to advance human-centered explainable AI.

The field of artificial intelligence (AI) is rapidly influencing health and healthcare, but bias and inadequate subgroup performance persists. Previou...