Latest AI and machine learning research in surgery for healthcare professionals.
Observing touch on another's body can elicit corresponding tactile sensations in the observer, a phenomenon termed mirror touch that supports empathy and social perception. This visuo-tactile resonance is thought to rely on structural correspondence between visual and somatosensory cortices, yet robotic systems lack computational frameworks that instantiate this principle. Here we demonstrate that...
Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an advanced stage, with an associated 5-year survival rate of about 30%. Early identification of non-responders to neoadjuvant chemotherapy remains a key unmet need, as it could prevent ineffective therapy and avoid delays in optimal surgical management. This work proposes a non-invasive deep learning...
Background. Commercial dental artificial intelligence in 2026 is overwhelmingly diagnostic: caries, calculus, periapical, and bone-level detection on ...
Medical multimodal large language models (MLLMs) have advanced image understanding and short-video analysis, but real clinical review often requires f...
Background: People with Multiple Long-Term Conditions (MLTC) experience higher rates of organ failure and death following cardiac surgery. The aim of ...
Background. Dengue has been a major health threat globally in recent years. In particular, dengue incidences continue to increase annually and the epi...
Background and objective: High-risk non-muscle-invasive bladder cancer (HR-NMIBC) is treated with transurethral resection and intravesical BCG instill...
Background: Integrating multimodal data into medical artificial intelligence (AI) tools and evaluating whether they outperform human experts remains a...
Abstract Objective: Structured extraction from clinical free-text depends on human annotators whose labels are susceptible to errors and knowledge-dri...
Real-world clinical data is inherently multimodal, providing complementary evidence that mirrors the practical necessity of jointly assessing multiple...
Grasp force estimation can help prevent robots from damaging delicate objects during manipulation and improve learning-based robotic control. Integrat...
Federated Multimodal Learning (FML) trains multimodal models across decentralized clients while keeping their image-text pairs private. However, joint...
Gastric cancer patients frequently experience skeletal muscle loss during the perioperative and adjuvant treatment period, which has been associated w...
Nasotracheal intubation (NTI) is a critical clinical procedure for establishing and maintaining patient airway patency. Machine-assisted NTI has emerg...
Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate as...
Peritoneal metastases are currently assessed using diagnostic laparoscopy to determine Sugarbaker's Peritoneal Cancer Index (sPCI), which works by div...
We reframe clinician overrides of clinical AI recommendations as implicit preference data - the same signal structure exploited by reinforcement learn...
Background and Objectives Preoperative prediction of functional outcomes in contrast-enhancing glioma could support surgical decision-making and patie...
Surgical training involves didactic teaching, mentor-led learning, surgical skills laboratories, and direct exposure to surgery; however, increasing c...
Accurate intraoperative assessment of glioma infiltration is essential for maximizing tumor resection while preserving functional brain tissue. Fluore...