Cancer immunology, immunotherapy : CII
Jun 4, 2024
BACKGROUND: The non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunother...
PURPOSE: The main objective of this study is to assess the possibility of using radiomics, deep learning, and transfer learning methods for the analysis of chest CT scans. An additional aim is to combine these techniques with bone turnover markers to...
OBJECTIVE: To assess the effectiveness of different machine learning models in estimating the pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II diagnosis, based on the clinical risk index determined by the a...
IMTRODUCTION: The high-risk population of patients with cardiovascular (CV) disease or risk factors (RF) suffering from COVID-19 is heterogeneous. Several predictors for impaired prognosis have been identified. However, with machine learning (ML) app...
Computer methods in biomechanics and biomedical engineering
Jun 3, 2024
Automated and early detection of diabetics with polyneuropathy in an ambulatory health monitoring setup may reduce the major risk factors for diabetic patients. Increased and localized plantar pressure associated with impaired pain and temperature is...
INTRODUCTION: Artificial intelligence (AI) is constantly developing in several medical areas and has become useful to assist with treatment planning. Orthodontics and maxillofacial surgery use AI-based technology to identify and select cephalometric ...
Journal of magnetic resonance imaging : JMRI
Jun 3, 2024
BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, highlighting the need to develop a robust, objective system for automatically detecting FLLs.
OBJECTIVE: To extract texture features from vocal cord leukoplakia (VCL) images and establish a VCL risk stratification prediction model using machine learning (ML) techniques.
OBJECTIVE: this study was to analyze the brain functional network of end-of-dose wearing-off (EODWO) in patients with Parkinson's disease (PD) using a convolutional neural network (CNN)-based functional magnetic resonance imaging (fMRI) data classifi...
BACKGROUND: The significance of diagnosing illnesses associated with brain cognitive and gait freezing phase patterns has led to a recent surge in interest in the study of gait for mental disorders. A more precise and effective way to characterize an...
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