NTHRYS › Internships › Ai Cancer Biology › AI Pathology Image Analysis Cancer Grading

Deep Learning Architectures for Histopathological Tumor Classification

Ai Cancer Biology

AI Pathology Image Analysis Cancer Grading

Variant

Pay · Join

Step 4 of 5Select variant

Field

▾

Category

▾

Focused area

▾

You might prefer

Explainable AI Methods for Pathologist Decision Support Systems Multi-Scale Feature Extraction from Histopathological Image Pyramids Weakly Supervised Learning for Cancer Grade Annotation in Pathology Domain Adaptation and Generalization Across Institutional Pathology Datasets Uncertainty Quantification in Deep Neural Networks for Cancer Grading Spatial Graph Neural Networks for Tumor Microenvironment Analysis Contrastive Learning and Self-Supervised Pretraining for Pathology Images Attention Mechanisms for Interpretable Morphological Feature Localization Federated Learning for Privacy-Preserving Multi-Center Cancer Grading

Ai Cancer Biology › AI Pathology Image Analysis Cancer Grading

Deep Learning Architectures for Histopathological Tumor Classification

This research investigates advanced convolutional neural network designs and transformer-based models for automated classification of tumor grades from whole-slide pathology images. The work produces novel architectural innovations that significantly improve diagnostic accuracy and establish new benchmarks for computational pathology applications.

🎓 TYPE

🌐 MODE

⏱

📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

Select your preferenceChoose Type, Mode, Duration to view Titles

Internship Type

Mode

Duration

🎯

Choose your preferences above

Select Type, Mode and Duration to view available internship titles and fees.