The purpose of the paper was to apply an Artificial Neural Networks with Radial Basis Function to develop an application model for diagnosing a subclinical ketosis type I and II in dairy cattle. While building the neural network model, applied method...
OBJECTIVES: We propose and test a framework to detect disease diagnosis using a recent large language model (LLM), Meta's Llama-3-8B, on French-language electronic health record (EHR) documents. Specifically, it focuses on detecting gout ('goutte' in...
INTRODUCTION: Gadolinium-based T1-weighted MRI sequence is the gold standard for the detection of active multiple sclerosis (MS) lesions. The performance of machine learning (ML) and deep learning (DL) models in the classification of active and non-a...
OBJECTIVES: This study aims to evaluate a deep learning pipeline for detecting clinically significant prostate cancer (csPCa), defined as Gleason Grade Group (GGG) ≥ 2, using biparametric MRI (bpMRI) and compare its performance with radiological read...
Journal of Nepal Health Research Council
Dec 19, 2024
BACKGROUND: Tuberculosis remains a public health challenge in Nepal and ranks as the seventh leading cause of death in the country. The END Tuberculosis strategy stresses - the screening for symptoms alone may not suffice; additional screening tools ...
Hong Kong medical journal = Xianggang yi xue za zhi
Dec 19, 2024
INTRODUCTION: Research concerning artificial intelligence in breast cancer detection has primarily focused on population screening. However, Hong Kong lacks a population-based screening programme. This study aimed to evaluate the potential of artific...
BACKGROUND: Alzheimer's Disease is a neurodegenerative condition leading to irreversible and progressive brain damage, with possible features such as structural atrophy. Effective precision diagnosis is crucial for slowing disease progression and red...
PURPOSE: Balancing surgical margins and functional outcomes is crucial during radical prostatectomy for prostate cancer. Stimulated Raman histology (SRH) is a novel, real-time imaging technique that provides histologic images of fresh, unprocessed, a...
Journal of gastroenterology and hepatology
Dec 17, 2024
BACKGROUND: Lugol chromoendoscopy has been shown to increase the sensitivity of detection of esophageal squamous cell carcinoma (ESCC). We aimed to develop a deep learning-based virtual lugol chromoendoscopy (V-LCE) method.
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