IEEE

IMed-CNN: Ensemble Learning Approach With Systematic Model Dropout for Enhanced Medical Image Classification Using Image Channels and Pixel Intervals

Abstract: To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...
gut.bmj

A fusion-based deep-learning algorithm predicts PDAC metastasis based on primary tumour CT images: a multinational study

Background Diagnosing the presence of metastasis of pancreatic cancer is pivotal for patient management and treatment, with contrast-enhanced CT scans (CECT) as the cornerstone of diagnostic ...
IEEE

Efficient Document Image Classification Using Deep Learning Enhance with CNN Architectures

Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
C&EN

To Fly, or Not to Fly, That Is the Question: A Deep Learning Model for Peptide Detectability Prediction in Mass Spectrometry

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Taken together, the specific characteristics and properties of ...
Frontiers

Enhanced breast cancer diagnosis using modified InceptionNet-V3: a deep learning approach for ultrasound image classification

Introduction: Breast cancer (BC) is a malignant neoplasm that originates in the mammary gland’s cellular structures and remains one of the most prevalent cancers among women, ranking second in ...