Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Objective: In the last two decades, there has been a growing interest in exploring surgical
procedures with statistical models to analyze operations at different semantic levels. This …

Surgical scene perception via videos is critical for advancing robotic surgery, telesurgery,
and AI-assisted surgery, particularly in ophthalmology. However, the scarcity of diverse and …

Surgical practice involves complex visual interpretation, procedural skills, and advanced
medical knowledge, making surgical vision-language pretraining (VLP) particularly …

Importance Competence in cataract surgery is a public health necessity, and videos of
cataract surgery are routinely available to educators and trainees but currently are of limited …

This study assessed the performance of automated machine learning (AutoML) in classifying
cataract surgery phases from surgical videos. Two ophthalmology trainees without coding …

Defocus blur is a persistent problem in microscope imaging that poses harm to pathology
interpretation and medical intervention in cell microscopy and microscope surgery. To …

This paper is a comprehensive survey of datasets for surgical tool detection and related
surgical data science and machine learning techniques and algorithms. The survey offers a …

The increase in chronic diseases has affected the countries' health system and economy.
With the recent COVID-19 virus, humanity has experienced a great challenge, which has led …

Abstract Models capable of leveraging unlabelled data are crucial in overcoming large
distribution gaps between the acquired datasets across different imaging devices and …