Abstract: Formal concept analysis (FCA) can formally model the correspondence between objects and attributes, which is crucial for single-label classification. The core of single-label classification ...

Electronic medical records (EMRs) enable healthcare institutions to digitally document patients’ clinical conditions, treatment processes, and diagnostic outcomes, supporting paperless clinical ...

Colon cancer classification has a significant guidance value in clinical diagnoses and medical prognoses. The classification of colon cancers with high accuracy is the premise of efficient treatment.

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

State Key Laboratory of Soil Pollution Control and Safety, and Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China ...

Deep learning model for multi-label thoracic disease detection from chest X-ray images using ResNet-50 and Grad-CAM visualization on the NIH ChestXray14 dataset.

Abstract: Multi-label text classification involves assigning multiple relevant categories to a single text, enabling applications in academic indexing, medical diagnostics, and e-commerce. However, ...

I tried applying label smoothing to my multi-label classification problem—given that my dataset is noisy and unbalanced, I thought it might help—but I ran into issue #40258 ...

In the published article, there was an error in the Funding statement. The Funding statement was erroneously omitted, and financial support grants should have instead ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...