In recent years, machine learning (ML) has become a buzzword in the field of medical
research, and its applications in surgery are rapidly expanding [1, 2]. With the development …

The exponential increase in the volume and complexity of healthcare data presents new
challenges to researchers and clinicians in analysis and interpretation. The requirement for …

Abstract Machine learning (ML) represents a collection of advanced data modeling
techniques beyond the traditional statistical models and tests with which most clinicians are …

Background Machine learning (ML) has garnered increasing attention as a means to
quantitatively analyze the growing and complex medical data to improve individualized …

Interest in the use of artificial intelligence (AI) and machine learning (ML) in medicine has
grown exponentially over the last few years. With its ability to enhance speed, precision, and …

Purpose An indication for surgical therapy includes balancing benefits against risk, which
remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical …

Abstract Machine learning (ML) is a collection of algorithms allowing computers to learn
directly from data without predetermined equations. It is used widely to analyze “big data”. In …

Background Machine learning (ML), a branch of artificial intelligence, involves the
development of algorithms focused on pattern recognition and learning for computer-based …

Background Machine learning (ML) has seen an increase in application, and is an important
element of a digital evolution. The role of ML within upper gastrointestinal surgery for …

Background Recent technological advances have led to the development and
implementation of machine learning (ML) in various disciplines, including neurosurgery. Our …