Advances in experimental medicine and biology
Jan 1, 2024
The introduction of "intelligent machines" goes back to Alan Turing in the 1940s. Artificial intelligence (AI) is a broad umbrella covering different methodologies, such as machine learning and deep learning. Deep learning, characterized by multilaye...
Advances in experimental medicine and biology
Jan 1, 2024
A large language model (LLM), in the context of natural language processing and artificial intelligence, refers to a sophisticated neural network that has been trained on a massive amount of text data to understand and generate human-like language. T...
Advances in experimental medicine and biology
Jan 1, 2024
"Bayesian Neural Networks in Predictive Neurosurgery" explains both conceptually and theoretically the combination of statistical techniques for clinical prediction models, including artificial neural networks, Bayesian regression, and Bayesian neura...
Advances in experimental medicine and biology
Jan 1, 2024
We present a gentle introduction to elementary mathematical notation with the focus of communicating deep learning principles. This is a "math crash course" aimed at quickly enabling scientists with understanding of the building blocks used in many e...
Advances in experimental medicine and biology
Jan 1, 2024
This chapter explores the transformative impact of deep learning (DL) on neurosurgery, elucidating its pivotal role in enhancing diagnostic performance, surgical planning, execution, and postoperative assessment. It delves into various deep learning ...
INTRODUCTION: The study hypothesizes that neural networks can be an effective tool for predicting treatment outcomes in patients with diabetic neovascular glaucoma (NVG), considering not only baseline intraocular pressure (IOP) values but also inflam...
Advances in experimental medicine and biology
Jan 1, 2024
Carotid artery (CA) stenosis (CAS) constitutes a significant factor to ischaemic cerebrovascular events which exhibiting no overt symptoms in the early stages. Early detection of CAS can prevent ischaemic stroke and improve patient prognosis. In this...
Decoding speech envelopes from electroencephalogram (EEG) signals holds potential as a research tool for objectively assessing auditory processing, which could contribute to future developments in hearing loss diagnosis. However, current methods stru...
Accurate prediction of echocardiographic parameters is essential for diagnosis and treatment of cardiac disease, especially for segmentation of the left ventricle to obtain measurements such as left ventricular ejection fraction and volume. However, ...
Cancer control : journal of the Moffitt Cancer Center
Jan 1, 2024
This study explored the application of meta-analysis and convolutional neural network-natural language processing (CNN-NLP) technologies in classifying literature concerning radiotherapy for head and neck cancer. It aims to enhance both the efficienc...
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