Latest AI and machine learning research in lymphoma for healthcare professionals.
The traditional risk management and control mode (RMCM) in regional sites has the defects of low eff...
PURPOSE: To improve the quantitative accuracy and diagnostic confidence of PET images reconstructed ...
Healthcare AI systems exclusively employ classification models for disease detection. However, with ...
BACKGROUND: Accurate prognostic prediction plays a crucial role in the clinical setting. However, th...
The major emission sources of NO are from automobiles, trucks, and various non-road vehicles, power ...
Whole genome sequencing is increasingly used to diagnose medical conditions of genetic origin. While...
Parallel imaging is the most clinically used acceleration technique for magnetic resonance imaging (...
Cell deformability is a useful feature for diagnosing various diseases (e.g., the invasiveness of ca...
The deployment of machine learning for tasks relevant to complementing standard of care and advancin...
Fluorescence imaging is increasingly being implemented in surgery. One of the drawbacks of its appli...
In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that ...
Lymphomas, or cancers of the lymphatic system, account for around half of all blood cancers diagnose...
Neuroblastoma is one of the most common pediatric cancers. This study used machine learning (ML) to ...
Classifying and analyzing human cells is a lengthy procedure, often involving a trained professional...
OBJECTIVE: The purpose of this study was to establish a deep-learning model for segmenting the cervi...
Within the next 1.5 decades, 1 in 7 U.S. adults is anticipated to suffer from age-related macular de...
OBJECTIVES: To demonstrate the effectiveness of automatic segmentation of diffuse large B-cell lymph...
PURPOSE: For the image classification problem, the construction of appropriate training data is impo...
Cross-domain decision-making systems are suffering a huge challenge with the rapidly emerging uneven...
A small dataset commonly affects generalization, robustness, and overall performance of deep neural ...
Nowadays, electric vehicles have gained great popularity due to their performance and efficiency. In...