Latest AI and machine learning research in surgery for healthcare professionals.
Contact-rich manipulation in unstructured environments demands precise, multimodal perception to e...
Percutaneous Coronary Intervention (PCI) is a minimally invasive procedure that improves coronary ...
Operating rooms (ORs) demand precise coordination among surgeons, nurses, and equipment in a fast-...
Optimal surgical methods require accurate prediction of extraction difficulty and complications. Alt...
Pelvic bone tumor resections remain significantly challenging due to complex three-dimensional ana...
Accurately localizing the brain regions that triggers seizures and predicting whether a patient wi...
Accurate classification of midpalatal suture maturation stages is critical for orthodontic diagnosis...
Fluoroscopically guided electrophysiology (EP) procedures expose operators to low doses of ionizing ...
Laparoscopic surgeries often suffer from reduced visual clarity due to the presence of surgical sm...
Traditional methods of surgical decision making heavily rely on human experience and prompt action...
In AI-empowered poster design, content-aware layout generation is crucial for the on-image arrange...
BACKGROUND: Pineal region tumors (PRTs) are rare but deep-seated brain tumors, and complete surgical...
Intra-operative data captured during image-guided surgery lacks sub-surface information, where key...
The integration of artificial intelligence (AI) and multiomics has transformed clinical and life sci...
This study aims to predict the optimal imaging parameters using a deep learning algorithm in 3D head...
This retrospective study leverages machine learning to determine the optimal timing for fracture rec...
BACKGROUND: The risks and prognosis of mild intracerebral hemorrhage (ICH) patients were easily over...
In laparoscopic surgery, a clear and high-quality visual field is critical for surgeons to make ac...
The high incidence and mortality rates of gastric cancer pose a significant burden on human health a...
Long text classification is challenging for Large Language Models (LLMs) due to token limits and h...
This paper presents a novel method for monocular patient-to-image intraoperative registration, spe...