Oncology/Hematology

Breast Cancer

Latest AI and machine learning research in breast cancer for healthcare professionals.

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Prediction methodology of air absorbed dose rates for Chinese cities with deep learning models.

Air absorbed dose rate is a key indicator of environmental radiation exposure. In China, automated e...

Self-HER2Net: A generative self-supervised framework for HER2 classification in IHC histopathology of breast cancer.

Breast cancer is a significant global health concern, where precise identification of proteins like ...

Radiation oncology patients' perceptions of artificial intelligence and machine learning in cancer care: A multi-centre cross-sectional study.

AIM: The use of artificial intelligence (AI) and machine learning (ML) is increasingly widespread in...

Role of artificial intelligence -based machine learning model in predicting HER2/neu gene status in breast cancer.

Our study investigated the predictive efficacy of AI-based Machine Learning (ML) model for determini...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting...

Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.

Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam ...

AGCLNDA: Enhancing the Prediction of ncRNA-Drug Resistance Association Using Adaptive Graph Contrastive Learning.

Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in chemotherapy resista...

Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.

Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, de...

Mammogram mastery: Breast cancer image classification using an ensemble of deep learning with explainable artificial intelligence.

Breast cancer is a serious public health problem and is one of the leading causes of cancer-related ...

Machine learning identifies SRD5A3 as a propionate-related prognostic biomarker in triple-negative breast cancer.

The increased risk of recurrence and metastasis are obstacles to treating TNBC. Propionate-related g...

Harnessing artificial intelligence to address immune response heterogeneity in low-dose radiation therapy.

Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its a...

Robotic radiation shielding system reduces radiation-induced DNA damage in operators performing electrophysiological procedures.

Fluoroscopically guided electrophysiology (EP) procedures expose operators to low doses of ionizing ...

Machine learning-driven imaging data for early prediction of lung toxicity in breast cancer radiotherapy.

One possible adverse effect of breast irradiation is the development of pulmonary fibrosis. The aim ...

[Integrated diagnosis and treatment of peritoneal metastasis in gastric cancer].

The high incidence and mortality rates of gastric cancer pose a significant burden on human health a...

Identification of molecular subtypes and a prognostic signature based on machine learning and purine metabolism-related genes in breast cancer.

Breast cancer (BC), one of the most prevalent malignant tumors worldwide, lacks efficacious diagnost...

Reconstruction of partially obscured objects with a physics-driven self-training neural network.

We investigate artificial-intelligence-supported in-line holographic imaging with coherent terahertz...

Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy.

Artificial intelligence (AI) incorporation into healthcare has proven revolutionary, especially in r...

The role of artificial intelligence in occupational health in radiation exposure: a scoping review of the literature.

INTRODUCTION: Artificial intelligence (AI) has the potential to significantly enhance workplace safe...

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer.

PURPOSE: Chemotherapy administration is a balancing act between giving enough to achieve the desired...

Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer.

Radiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patien...

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, c...

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