Oncology/Hematology

Breast Cancer

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

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AI for image quality and patient safety in CT and MRI.

Substantial endeavors have been recently dedicated to developing artificial intelligence (AI) soluti...

From text to insight: A natural language processing-based analysis of burst and research trends in HER2-low breast cancer patients.

With the intensification of population aging, the proportion of elderly breast cancer patients is co...

Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis.

The viability of cells and the integrity of the genome depend on the detection and repair of damaged...

Soft-tissue metastasis in esophageal cancer managed by dose escalation radiation therapy: a clinical case and review of literature.

Soft tissue metastasis in esophageal cancer is a very rare entity. A 76-year-old man was referred fo...

Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.

Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year o...

Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms.

Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystem...

Radiation oncology at crossroads: Rise of AI and managing the unexpected.

Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflo...

CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.

RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some es...

Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy.

PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom ...

MLAR-UNet: LDCT image denoising based on U-Net with multiple lightweight attention-based modules and residual reinforcement.

Computed tomography (CT) is a crucial medical imaging technique which uses x-ray radiation to identi...

Monitoring Immunohistochemical Staining Variations Using Artificial Intelligence on Standardized Controls.

Quality control of immunohistochemistry (IHC) slides is crucial to ascertain accurate patient manage...

DeepInterAware: Deep Interaction Interface-Aware Network for Improving Antigen-Antibody Interaction Prediction from Sequence Data.

Identifying interactions between candidate antibodies and target antigens is a key step in developin...

Does Deep Learning Reconstruction Improve Ureteral Stone Detection and Subjective Image Quality in the CT Images of Patients with Metal Hardware?

Diagnosing ureteral stones with low-dose CT in patients with metal hardware can be challenging beca...

A promising AI based super resolution image reconstruction technique for early diagnosis of skin cancer.

Skin cancer can be prevalent in people of any age group who are exposed to ultraviolet (UV) radiatio...

Machine learning prediction of breast cancer local recurrence localization, and distant metastasis after local recurrences.

Local recurrences (LR) can occur within residual breast tissue, chest wall, skin, or newly formed sc...

An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Mammography is the recommended imaging modality for breast cancer screening. Expressions of human ep...

Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy.

INTRODUCTION: For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 ...

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