Latest AI and machine learning research in surgery for healthcare professionals.
The global demand for cosmetic procedures is accelerating, with over 1.6 million aesthetic surgical procedures performed in the US in 2023. Concurrently, AI is transforming surgical practice through advanced analytics, predictive modeling, and computer vision. Cosmetic surgery, characterized by subjective outcomes and limited standardized metrics, presents a unique opportunity for AI integration t...
Artificial intelligence (AI) is increasingly integrated into plastic and reconstructive surgery. It supports preoperative prediction and imaging analysis, intraoperative visualization, and postoperative monitoring. While these advancements demonstrate AI's growing potential across the surgical continuum, their adoption also presents ethical, legal, and regulatory challenges. Concerns surrounding a...
Rectal cancer management has increasingly shifted toward organ-preserving strategies that aim to maintain oncologic control while preserving bowel, ur...
BACKGROUND: Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are heterogeneous tumors with rising incidence, necessitating precise preoperat...
Artificial intelligence (AI) has become pervasive in and beyond plastic surgery. Myriad applications exist, and patients and plastic surgeons are incr...
OBJECTIVE: To develop and validate a deep learning system (DLS) model predicting hematoma expansion (HE) based on non-contrast (NC) CT and a score com...
Robot-aided rehabilitation effectively supports treatment of upper-limb disorders and enhances outcomes when combined with traditional therapy. Artifi...
BACKGROUND: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrom...
BACKGROUND: Predicting futile recanalisation following endovascular treatment (EVT) in patients with large core infarctions is crucial for guiding cli...
To construct an efficient predictive model for post-lung cancer resection delirium (POD) using artificial intelligence, with a focus on leveraging syn...
In orthognathic surgery, accurate segmentation of the pterygopalatine and mandibular canals in maxillofacial cone beam computed tomography (CBCT) scan...
Wearable microneedles (MNs) biosensors offer significant potential for minimally invasive biomarker detection in interstitial fluid (ISF). However, su...
INTRODUCTION: Accurate and objective assessment of operative skills is essential for improving training paradigms, patient safety, and quality of surg...
BACKGROUND: Despite the ongoing controversy around the prophylactic use of antiseizure medications (ASMs) in seizure-naïve patients undergoing brain t...
BACKGROUND AND OBJECTIVES: Days alive and at home (DAH) is a validated outcome measure that captures health care transitions between time spent at hom...
OBJECTIVE: The optimal treatment for distal medium vessel occlusion (DMVO) stroke remains uncertain, and evidence comparing endovascular therapy (EVT)...
BACKGROUND: Artificial intelligence (AI), particularly large language models (LLMs), has demonstrated potential to improve patient communication by de...
BACKGROUND: T1 colorectal cancer (T1 CRC) is increasingly treated with curative-intent endoscopic resection, but tumor recurrence remains a critical f...
Lung cancer remains the leading cause of cancer-related incidence and mortality worldwide. Its tendency for postoperative distant metastasis significa...
AIM: This study aimed to develop a machine learning (ML)-assisted model to predict the risk of upstaging (subsequent higher stage on repeat pathology)...