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...
BACKGROUND: Colonoscopy can detect colorectal adenomas and reduce the incidence of colorectal cancer, but there are still many missing diagnoses. Artificial intelligence-assisted colonoscopy (AIAC) can effectively reduce the rate of missed diagnosis ...
BACKGROUND: Artificial intelligence system is a deep learning system based on computer-assisted ultrasonic image diagnosis, which can extract morphological features of breast mass and conduct objective and efficient image analysis, thus automatically...
INTRODUCTION: Thoracic diseases include a variety of common human primary malignant tumors, among which lung cancer and esophageal cancer are among the top 10 in cancer incidence and mortality. Early diagnosis is an important part of cancer treatment...
BACKGROUND: Although many machine learning algorithms have been developed to detect anterior cruciate ligament (ACL) injury based on magnetic resonance imaging (MRI), the performance of different algorithms required further investigation. The objecti...
INTRODUCTION: Prediction of pain using machine learning algorithms is an emerging field in both computer science and clinical medicine. Several machine algorithms were developed and validated in recent years. However, the majority of studies in this ...
OBJECTIVES: Despite their essential role in collecting and organizing published medical literature, indexed search engines are unable to cover all relevant knowledge. Hence, current literature recommends the inclusion of clinical trial registries in ...
Comparative biochemistry and physiology. Part D, Genomics & proteomics
Mar 1, 2018
In order to understand the mechanisms underlying stress responses, meta-analysis of transcriptome is made to identify differentially expressed genes (DEGs) and their biological, molecular and cellular mechanisms in response to stressors. The present ...
MOTIVATION: Supervised machine learning is widely applied to transcriptomic data to predict disease diagnosis, prognosis or survival. Robust and interpretable classifiers with high accuracy are usually favored for their clinical and translational pot...