Recent advances in artificial intelligence (AI) have sparked a surge in the application of
computer vision (CV) in surgical video analysis. Laparoscopic surgery produces a large …

Background Minimally invasive surgery is complex and associated with substantial learning
curves. Computer-aided anatomy recognition, such as artificial intelligence-based …

Aims Heart failure (HF) with preserved ejection fraction (HFpEF) is a complex syndrome with
a poor prognosis. Phenoty** is required to identify subtype‐dependent treatment …

Purpose Image segmentation of instruments in the raw surgical videos is a critical
component of intraoperative assistance softwares. Challenges include addressing rendered …

Multi-instance multi-label learning (MIML), which deals with objects with complex structures
and multiple semantics, plays a crucial role in various fields. In practice, the naturally …

Abstract Analysis of operative data with convolutional neural networks (CNNs) is expected to
improve the knowledge and professional skills of surgeons. Identification of objects in videos …

Purpose In this study, we propose a deep learning approach for assessment of gallbladder
(GB) wall vascularity from images of laparoscopic cholecystectomy (LC). Difficulty in the …

Recently, the usage of machine learning algorithms is subject to discussion from a legal and
ethical point of view. Unwanted discrimination regarding gender or race of a prediction …

Background Devices that help educate young doctors and enable safe, minimally invasive
surgery are needed. Eureka is a surgical artificial intelligence (AI) system that can …

Real-world applications always contain complex data objects with multiple semantics. The
machine learning tasks generalized from these applications can be formulated as multi …