Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
Ovarian cancer, with high mortality, demands accurate preoperative assessment to guide individualized treatment. It typically requires ultrasound, CT, and MRI interpreted by multidisciplinary teams (MDTs) in complex cases. We developed OVUCM, a multi-task AI system that integrates multi-modalities via intermediate fusion using radiomics, machine learning, and 5×4 nested cross-validation. Trained o...
» Artificial intelligence (AI) is increasingly integrated across the total hip and knee arthroplasty care continuum, including preoperative risk stratification and templating, intraoperative computer-vision guidance and robotic assistance, and postoperative complication detection and outcome prediction. » Machine-learning models often outperform traditional statistical approaches in predicting com...
OBJECTIVES: To determine whether pretreatment radiomics can predict medication-related osteonecrosis of the jaw (MRONJ). METHODS: Patients with mandib...
BACKGROUND AND OBJECTIVE: Accurately predicting outcomes in extremely preterm infants remains a major challenge in neonatology. Traditional scores suc...
BACKGROUND: Preterm birth, defined as delivery before 37 weeks of gestation, is a major cause of neonatal morbidity and mortality and places a substan...
The Agricultural Multidisciplinary Collection Dataset (AMCD) contains 5405 JPG images of agricultural crops and flowers collected in Bangladesh. The i...
BACKGROUND: Burnout affects nearly half of physicians in the United States, with emergency physicians (EPs) at particularly high risk. Documentation b...
BACKGROUNDS: Haematoma expansion (HE) is a significant factor in poor outcomes following intracerebral haemorrhage (ICH). Studies have suggested that ...
Diabetes technology has transformed substantially over the past two decades, becoming central to modern diabetes management. Continuous glucose monito...
BACKGROUND: Accurate clinical outcome prediction using electronic health records (EHRs) is crucial for patient care and resource allocation. EHRs incl...
BACKGROUND: Telehealth expansion and artificial intelligence (AI) adoption are often described as parallel dimensions of health system digital transfo...
Partial Discharge (PD) is one of the most critical factors contributing to the degradation of insulation systems in power transformers. Early detectio...
Accurate timing prediction of surgery is essential for efficient operating room scheduling and ensuring patient care. This study proposes a two-layere...
Large language models (LLMs) like GPT have been proposed to support complex clinical decision-making. This study evaluated the performance of GPT-base...
PURPOSE OF REVIEW: Neuropathic pain remains challenging due to its heterogeneous mechanisms and variable treatment response. This narrative review eva...
BACKGROUND: Ventilator-induced diaphragm dysfunction (VIDD) is a frequent and under-recognized consequence of prolonged mechanical ventilation in inte...
Patient-specific computational tools hold great promise for the development of more personalized treatment strategies for acute respiratory failure. S...
BACKGROUND: Vaginal birth after two cesarean deliveries (VBAC2) is increasingly recognized as a reasonable and, in selected cases, preferable option. ...
BACKGROUND: Effective physician-patient communication is essential for building trust and sustaining positive relationships, yet becomes increasingly ...
Progressive pulmonary fibrosis (PPF) remains difficult to predict because static imaging may not fully capture regional respiratory motion, ventilatio...