Latest AI and machine learning research in surgery for healthcare professionals.
Artificial intelligence (AI) increasingly influences facial aesthetic standards, alongside the judgment of the surgeon and the goals of the patient. Systems that score, edit, generate, and curate facial images now encode explicit, quantitative definitions of attractiveness, derived from rated image data sets and delivered to the public through attractiveness-prediction algorithms, augmented-realit...
GOALS: To compare a vision transformer with 2 convolutional neural network architectures for multiclass lesion classification in capsule endoscopy images. BACKGROUND: Manual review of capsule endoscopy is time-consuming and subject to interobserver variability. Deep learning can automate lesion recognition; however, most prior capsule endoscopy work evaluates a small number of classes, and systema...
BACKGROUND AND OBJECTIVES: MRI and computed tomography (CT) are commonly combined to localize intracranial electrodes in deep brain stimulation (DBS)....
Bladder cancer remains a major global health challenge, necessitating rigorous endoscopic surveillance and the precise identification of neoplastic le...
BACKGROUND: Peer-reviewed medical literature consistently violates established health literacy readability targets, creating a gap that effectively ex...
BACKGROUND: Early risk stratification in emergency medical services (EMS) is essential for patients presenting with acute cardiopulmonary symptoms, ye...
OBJECTIVE: Cervical spondylotic myelopathy (CSM) is a leading cause of spinal cord dysfunction requiring surgical intervention. Prolonged length of st...
OBJECTIVE: Renal cell carcinoma (RCC) is a common malignancy that metastasizes to the spine, leading to complex treatment challenges and reduced survi...
BACKGROUND: Digitalisation, and in particular the use of artificial intelligence (AI), is becoming increasingly important in medicine. At the same tim...
AIM: To evaluate the impact of adding early processed quantitative EEG biomarkers to health record data for early neurological risk stratification aft...
INTRODUCTION: Red blood cell (RBC) transfusions are frequently administered in the intensive care unit (ICU) and are independently associated with inc...
Accurately distinguishing the benign thyroid nodules (BTNs) and malignant thyroid nodules (MTNs) is crucial for treatment planning and prognosis. This...
Bacterial infections represent a critical threat to neonatal health, accounting for approximately 25% of neonatal mortality globally. Timely and preci...
Pituitary macroadenomas (PMAs) are among the most common intracranial tumors and pose significant surgical challenges, especially when the tumor consi...
To systematically characterize the global research trends, knowledge structure, thematic hotspots, and frontier evolution of artificial intelligence (...
Causal questions have long been central to psychological research, particularly in randomized experiments, while formal causal-inference methods are i...
OBJECTIVES: To evaluate the feasibility and accuracy of an artificial intelligence (AI) model to assist surgeons through automated real-time detection...
OBJECTIVE: To compare the diagnostic accuracy of four available automated electronic medical record (EMR) retrieval methods, including a large languag...
BACKGROUND: Accurately predicting operative difficulty in laparoscopic cholecystectomy (LC) is foundational to personalized surgical planning and pati...
BACKGROUND AND OBJECTIVES: Patients with temporal lobe epilepsy (TLE) can achieve seizure freedom in the early period after surgery, yet up to half ex...