Cardiovascular

RadField3D: A Data Generator and Data Format for Deep Learning in Radiation-Protection Dosimetry for Medical Applications

In this research work, we present our open-source Geant4-based Monte-Carlo simulation application,...

Reliable Breast Cancer Molecular Subtype Prediction based on uncertainty-aware Bayesian Deep Learning by Mammography

Breast cancer is a heterogeneous disease with different molecular subtypes, clinical behavior, tre...

DLSOM: A Deep learning-based strategy for liver cancer subtyping

Liver cancer is a leading cause of cancer-related mortality worldwide, with its high genetic heter...

Kinetic-Diffusion-Rotation Algorithm for Dose Estimation in Electron Beam Therapy

Monte Carlo methods are state-of-the-art when it comes to dosimetric computations in radiotherapy....

End-to-end Triple-domain PET Enhancement: A Hybrid Denoising-and-reconstruction Framework for Reconstructing Standard-dose PET Images from Low-dose PET Sinograms

As a sensitive functional imaging technique, positron emission tomography (PET) plays a critical r...

State-of-the-Art Deep Learning CT Reconstruction Algorithms in Abdominal Imaging.

The implementation of deep neural networks has spurred the creation of deep learning reconstruction ...

Monitoring Over Time of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients Through an Ensemble Vision Transformers-Based Model.

BACKGROUND: Morphological and vascular characteristics of breast cancer can change during neoadjuvan...

Explainable Machine Learning Predictions for the Benefit From Chemotherapy in Advanced Non-Small Cell Lung Cancer Without Available Targeted Mutations.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a global health challenge. Chemotherapy remains th...

Evaluation of machine learning algorithms and computational structural validation of CYP2D6 in predicting the therapeutic response to tamoxifen in breast cancer.

OBJECTIVE: CYP2D6 plays a critical role in metabolizing tamoxifen into its active metabolite, endoxi...

Semi-analytical model for the calculation of solar radiation pressure and its effects on a LEO satellite with predicting the change in position vectors using machine learning techniques

The rapid increase in the deployment of Low Earth Orbit (LEO) satellites, catering to diverse appl...

NACNet: A Histology Context-aware Transformer Graph Convolution Network for Predicting Treatment Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) response prediction for triple negative breast cancer (TNBC) patien...

Equivariant Graph Attention Networks with Structural Motifs for Predicting Cell Line-Specific Synergistic Drug Combinations

Cancer is the second leading cause of death, with chemotherapy as one of the primary forms of trea...

Leveraging Transfer Learning and Multiple Instance Learning for HER2 Automatic Scoring of H\&E Whole Slide Images

Expression of human epidermal growth factor receptor 2 (HER2) is an important biomarker in breast ...

PathoGen-X: A Cross-Modal Genomic Feature Trans-Align Network for Enhanced Survival Prediction from Histopathology Images

Accurate survival prediction is essential for personalized cancer treatment. However, genomic data...

Exploring prognostic biomarkers in pathological images of colorectal cancer patients via deep learning.

Hematoxylin and eosin (H&E) whole slide images provide valuable information for predicting prognosti...

Revolutionizing Personalized Cancer Vaccines with NEO: Novel Epitope Optimization Using an Aggregated Feed Forward and Recurrent Neural Network with LSTM Architecture

As cancer cases continue to rise, with a 2023 study from Zhejiang and Harvard predicting a 31 perc...

Computational Pathology for Accurate Prediction of Breast Cancer Recurrence: Development and Validation of a Deep Learning-based Tool

Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cance...

Active learning for energy-based antibody optimization and enhanced screening

Accurate prediction and optimization of protein-protein binding affinity is crucial for therapeuti...

Development and validation of machine learning models for predicting HER2-zero and HER2-low breast cancers.

OBJECTIVES: To develop and validate machine learning models for human epidermal growth factor recept...

Tailored chemotherapy: Innovative deep-learning model customizing chemotherapy for high-grade serous ovarian carcinoma.

Interpretable breast cancer classification using CNNs on mammographic images

Deep learning models have achieved promising results in breast cancer classification, yet their 'b...