AIMC Topic: Artificial Intelligence

Clear Filters Showing 24241 to 24250 of 26332 articles

The Artificial Intelligence Doctor: Considerations for the Clinical Implementation of Ethical AI.

Acta neurochirurgica. Supplement
The applications of artificial intelligence (AI) and machine learning (ML) in modern medicine are growing exponentially, and new developments are fast-paced. However, the lack of trust and appropriate legislation hinder its clinical implementation. R...

Machine Learning and Ethics.

Acta neurochirurgica. Supplement
When new technology is introduced into healthcare, novel ethical dilemmas arise in the human-machine interface. As artificial intelligence (AI), machine learning (ML) and big data can exhaust human oversight and memory capacity, this will give rise t...

Foundations of Multiparametric Brain Tumour Imaging Characterisation Using Machine Learning.

Acta neurochirurgica. Supplement
The heterogeneity of brain tumours at the molecular, metabolic and structural levels poses significant challenge for accurate tissue characterisation. Artificial intelligence and radiomics have emerged as valuable tools to analyse quantitative featur...

Foundations of Lesion Detection Using Machine Learning in Clinical Neuroimaging.

Acta neurochirurgica. Supplement
This chapter describes technical considerations and current and future clinical applications of lesion detection using machine learning in the clinical setting. Lesion detection is central to neuroradiology and precedes all further processes which in...

Machine Learning-Based Radiomics in Neuro-Oncology.

Acta neurochirurgica. Supplement
In the last decades, modern medicine has evolved into a data-centered discipline, generating massive amounts of granular high-dimensional data exceeding human comprehension. With improved computational methods, machine learning and artificial intelli...

Machine Learning Algorithms in Neuroimaging: An Overview.

Acta neurochirurgica. Supplement
Machine learning (ML) and artificial intelligence (AI) applications in the field of neuroimaging have been on the rise in recent years, and their clinical adoption is increasing worldwide. Deep learning (DL) is a field of ML that can be defined as a ...

A Discussion of Machine Learning Approaches for Clinical Prediction Modeling.

Acta neurochirurgica. Supplement
While machine learning has occupied a niche in clinical medicine for decades, continued method development and increased accessibility of medical data have led to broad diversification of approaches. These range from humble regression-based models to...

Foundations of Machine Learning-Based Clinical Prediction Modeling: Part I-Introduction and General Principles.

Acta neurochirurgica. Supplement
We provide explanations on the general principles of machine learning, as well as analytical steps required for successful machine learning-based predictive modeling, which is the focus of this series. In particular, we define the terms machine learn...

Machine Intelligence in Clinical Neuroscience: Taming the Unchained Prometheus.

Acta neurochirurgica. Supplement
The democratization of machine learning (ML) through availability of open-source learning libraries, the availability of datasets in the "big data" era, increasing computing power even on mobile devices, and online training resources have both led to...

Distinguishing Intramedullary Spinal Cord Neoplasms from Non-Neoplastic Conditions by Analyzing the Classic Signs on MRI in the Era of AI.

Current medical imaging
Intramedullary lesions can be challenging to diagnose, given the wide range of possible pathologies. Each lesion has unique clinical and imaging features, which are best evaluated using magnetic resonance imaging. Radiological imaging is unique with ...