Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
BACKGROUND: Artificial intelligence (AI) is expected to introduce an increasing number of biomarkers in oncology. To bridge the gap between oncology and computer science, it is timely to define recommendations for AI-based biomarkers suitable for routine clinical use. Here, we propose the ESMO (European Society for Medical Oncology) Basic Requirements for AI-based Biomarkers In Oncology (EBAI). DE...
BACKGROUND: Depression presents with heterogeneity in symptom trajectories, complicating individualized treatment. Identifying distinct classes of symptom trajectories and their predictors may enable earlier intervention for those at greatest risk of poor outcomes. METHODS: We analyzed 620 inpatients with depression drawn from two independent naturalistic samples. Using Growth Mixture Modeling, la...
BACKGROUND: Among traumatic-fracture patients admitted to intensive care units (ICUs), those with substantial chronic comorbidities recover more slowl...
ObjectiveThe mandibular symphysis is a donor site for alveolar bone grafting (ABG) in patients with cleft lip and/or palate, offering reduced morbidit...
BACKGROUND AND OBJECTIVE: Overcrowding in emergency departments (EDs) remains a critical challenge in healthcare systems. Accurate forecasting of pati...
BACKGROUND: Distal radial fractures (DRFs) are some of the most common pediatric injuries, often involving the physis. Diagnostic accuracy can be chal...
BACKGROUND: Breast cancer (BC) treatment efficacy is often compromised by tumor cell plasticity and multidrug resistance of multi-factorial origin. Am...
Identifying relevant input features which contribute to the output of a clinical prediction model can enhance the model explainability. To allow the e...
OBJECTIVES: The aim of this analysis was to investigate the historical development, current status, and research hotspots related to the application o...
OBJECTIVE: This study has two main objectives: (1) to develop a multi-model framework for predicting Intensive Care Unit (ICU) mortality within the fi...
BACKGROUND: Minimizing postoperative complications is imperative to improving patient outcomes. The purpose of this investigation is to develop machin...
BACKGROUND: The Hypotension Prediction Index (HPI) is a machine-learning algorithm designed to predict hypotension. by maintaining mean arterial press...
BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by physical or emotional stress, involving complex multi...
BACKGROUND: Low health literacy affects nearly one-third of adults in the United States, and almost 68 million Americans speak a language other than E...
Background: Acute Kidney Injury (AKI), a leading organ failure cause in critical patients, demands early high-risk identification to enhance outcomes....
As an endocrine-disrupting chemical, 4-nonylphenol (4-NP) has been found above safe limits in global water systems and associated with cancer progress...
Extracorporeal membrane oxygenation (ECMO) has emerged as a critical intervention in the management of patients with end-stage lung disease undergoing...
BACKGROUND: The prevalence of malnutrition is common in hospitalized patients. Timely and efficient nutrition support can improve clinical outcomes an...
ObjectiveWith the rapid adoption of artificial intelligence (AI) technologies by adolescents, the impact on their mental health is of critical concern...
INTRODUCTION: Efforts are being made to design a brain-like intelligence due to its robustness, synaptic modification (i.e., learning and memory), ana...