A study has found that the way medical images are prepared before analysis can have a significant impact on the performance of deep learning models.

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...

Development and Portability of a Text Mining Algorithm for Capturing Disease Progression in Electronic Health Records of Patients With Stage IV Non–Small Cell Lung Cancer Emerging evidence suggests ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, ...

The Santiago Urban Dataset (SUD) is a new, composite dataset merging handheld mobile laser scanning (HMLS) and mobile laser ...

A recent Scientific Reports study discusses the potential of retinal fundus imaging as a diagnostic screening modality for Parkinson's disease (PD). Study: Deep learning predicts prevalent and ...

Master’s thesis position (M.Sc. student) in Deep Learning for Healthcare.

Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new possibilities and reshaping industries. Despite its prevalence, ...

Alongside the model, a high-quality benchmark dataset covering 101 pest and disease classes has been publicly released. Together, they offer a ...

Using a custom "camera-to-rice" platform combined with deep-learning methods for feature extraction, matching, segmentation, and denoising, the system ...