Latest AI and machine learning research in surgery for healthcare professionals.
Diabetic retinopathy (DR) is a frequent complication of diabetes, affecting millions worldwide. Screening for this disease based on fundus images has been one of the first successful use cases for modern artificial intelligence in medicine. However, current state-of-the-art systems typically use black-box models to make referral decisions, requiring post-hoc methods for AI-human interaction and cl...
AIM: This study aimed to evaluate the effect of esketamine on perioperative anxiety and depressive symptoms, acute stress reaction, and serum neurotransmitters in patients undergoing total hysterectomy.
OBJECTIVE: This study aims to evaluate the feasibility of video-based assessment rate of Critical Views of Safety criteria for sentinel lymph node dis...
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative...
Non-muscle-invasive bladder cancer (NMIBC) is a relentless challenge in oncology, with recurrence rates soaring as high as 70-80%. Each recurrence t...
Precise manipulation tasks require accurate knowledge of payload inertial parameters. Unfortunately, identifying these parameters for unknown payloa...
Diabetic retinopathy is a severe eye condition caused by diabetes where the retinal blood vessels get damaged and can lead to vision loss and blindn...
Goal: A limitation in robotic surgery is the lack of force feedback, due to challenges in suitable sensing techniques. To enhance the perception of ...
With the increasing use of surgical robots in clinical practice, enhancing their ability to process multimodal medical images has become a key resea...
Robotic-assisted joint reconstruction has gradually become a routine procedure in clinical practice. Robots enhance surgical precision, minimize soft ...
The automatic summarization of surgical videos is essential for enhancing procedural documentation, supporting surgical training, and facilitating p...
The development of autonomous robotic systems offers significant potential for performing complex tasks with precision and consistency. Recent advan...
Brenier proved that under certain conditions on a source and a target probability measure there exists a strictly convex function such that its grad...
Teleoperation is crucial for hazardous environment operations and serves as a key tool for collecting expert demonstrations in robot learning. Howev...
Most existing robot manipulation methods prioritize task learning by enhancing perception through complex deep network architectures. However, they ...
Robot-assisted minimally invasive surgeries offer many advantages but require complex motor tasks that take surgeons years to master. There is curre...
This paper presents a dynamic arthroscopic navigation system based on multi-level memory architecture for anterior cruciate ligament (ACL) reconstru...
Advancements in machine learning have revolutionized preoperative risk assessment. In this article, we comment on the article by Huang , which present...
Patients with neurological conditions require rehabilitation to restore their motor, visual, and cognitive abilities. To meet the shortage of therap...
Purpose: Automated Surgical Phase Recognition (SPR) uses Artificial Intelligence (AI) to segment the surgical workflow into its key events, function...