Latest AI and machine learning research in lymphoma for healthcare professionals.
Computer-assisted algorithms have become a mainstay of biomedical applications to improve accuracy a...
Convolutional neural networks have established themselves over the past years as the state of the ar...
Lung cancer is a leading cause of cancer death in both men and women worldwide. The high mortality r...
The unique physical embodiment of robots enables physical contact between machines and humans. Since...
Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We in...
Radical prostatectomy is the gold standard in patients that are surgical candidates with localized p...
Brain image analysis has advanced substantially in recent years with the proliferation of neuroimagi...
Contamination is a critical issue that affects food consumption adversely. Therefore, efficient dete...
Integrating large single-cell gene expression, chromatin accessibility and DNA methylation datasets ...
Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated de...
Sensor technologies and data collection practices are changing and improving quality metrics across...
To evaluate the performance of the classic machine learning algorithms and the effectiveness of vari...
PURPOSE: To determine classification criteria for intermediate uveitis, non-pars planitis type (IU-N...
Evidence has accumulated enough to prove non-coding RNAs (ncRNAs) play important roles in cellular b...
OBJECTIVES: Attenuation correction (AC) is crucial for ensuring the quantitative accuracy of positro...
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays imag...
Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop...
Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it c...
Consumption of copper and aluminum has increased significantly in recent years; therefore, recycling...
PURPOSE: To explore a new approach mainly based on deep learning residual network (ResNet) to detect...
A statistical framework for non-negative matrix factorization based on generalized dual Kullback-Lei...