Oncology/Hematology

Breast Cancer

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

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Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristic...

Artificial intelligence for response prediction and personalisation in radiation oncology.

Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multiface...

An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.

RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before tre...

The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists.

The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-a...

Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy.

RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of the deep learning radiomics ...

Deep reinforcement learning control of combined chemotherapy and anti-angiogenic drug delivery for cancerous tumor treatment.

By virtue of the chronic and dangerous nature of cancer, researchers have explored various approache...

Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.

OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) v...

Machine learning to predict completion of treatment for pancreatic cancer.

BACKGROUND: Chemotherapy enhances survival rates for pancreatic cancer (PC) patients postsurgery, ye...

Deep reinforcement learning in radiation therapy planning optimization: A comprehensive review.

PURPOSE: The formulation and optimization of radiation therapy plans are complex and time-consuming ...

Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides.

BACKGROUND: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has emerged as a new s...

Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy.

Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dos...

Automatic localization of anatomical landmarks in head cine fluoroscopy images via deep learning.

BACKGROUND: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; per...

A machine learning-based pipeline for multi-organ/tissue patient-specific radiation dosimetry in CT.

OBJECTIVES: To develop a machine learning-based pipeline for multi-organ/tissue personalized radiati...

Artificial Intelligence for Radiation Treatment Planning: Bridging Gaps From Retrospective Promise to Clinical Reality.

Artificial intelligence (AI) radiation therapy (RT) planning holds promise for enhancing the consist...

Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer.

PURPOSE: Conventional normal tissue complication probability (NTCP) models for patients with head an...

Deep learning applied to dose prediction in external radiation therapy: A narrative review.

Over the last decades, the use of artificial intelligence, machine learning and deep learning in med...

Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application.

BACKGROUND: Radiotherapy has been crucial in prostate cancer treatment. However, manual segmentation...

A multicenter study on deep learning for glioblastoma auto-segmentation with prior knowledge in multimodal imaging.

A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for r...

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