Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
Hospital readmissions represent a persistent challenge for healthcare systems, often stemming from inadequate post-discharge monitoring. This study presents a Machine Learning (ML)-driven Clinical Decision Support System (CDSS) designed to enhance nursing risk assessment in post-discharge care. Developed using a Design Science Research Methodology, the artefact integrates a digital questionnaire, ...
Prognostication in patient with out-of-hospital cardiac arrest (OHCA) underwent extracorporeal cardiopulmonary resuscitation (ECPR) remains challenging due to the complexity of clinical variables. We aimed to develop and interpret artificial intelligence (AI) models for early outcome prediction in OHCA patients treated with ECPR, and to identify clinically meaningful patient subgroups through supe...
Accurately distinguishing between epileptic seizures (ES) and nonepileptic seizures (NES) is a significant clinical challenge that typically requires ...
Any tool that can reduce the administrative burden on healthcare providers while preserving safe, accountable and high-quality medical documentation i...
Timely admission to the emergency department is a crucial determinant of patient outcomes. Conversely, unnecessary hospital admissions can overburden ...
Non-contrast CT head scans (NCCTH) are the most frequently requested cross-sectional imaging in the Emergency Department. While AI tools have been dev...
Artificial intelligence (AI) applied to routine electrocardiograms (ECGs) offers promise for screening of structural heart disease (SHD), yet broad cl...
Intravenous (IV) fluids are cornerstone for management of acute kidney injury (AKI) after sepsis but can cause fluid overload. Restrictive fluid strat...
Sepsis remains a major cause of preventable pediatric hospital deaths in developing countries, with progress hindered by the lack of effective risk id...
Large language models (LLMs) have been investigated for clinical documentation, with concerns about hallucinations and factual errors. Clinician revie...
Frailty and multimorbidity are common in older adults and contribute substantially to prolonged hospitalizations, readmissions, and mortality. Yet, ex...
Accurate clinical and pathological diagnoses are essential in neurodegenerative diseases, especially given the emergence of pathology-specific disease...
Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted scr...
Dementia encompasses diverse clinical syndromes where diseases of the brain can manifest as impaired cognitive abilities, such as in Alzheimer’s disea...
In active vision, the brain receives and encodes discontinuous streams of visual information gated by saccadic eye movements. Saccadic modulation of n...
Psychotropic medications are commonly used for children with neurodevelopmental conditions, but their effectiveness varies, making treatment selection...
Timely intensive rehabilitation is crucial to contrast the negative escalation of events that follow a stroke injury, to promote tissue regeneration, ...
Quantification of ischemic brain tissue on non-contrast CT (NCCT) in acute ischemic stroke is challenging in the acute setting. To compare the spatial...
Chronic Kidney Disease (CKD) is a progressive condition requiring evidence-based management, but adherence to complex guidelines remains challenging. ...
Large language models can help with clinical decision-making tasks. Complex oncology cases are best managed through multidisciplinary tumor boards but...