Breast Cancer

Correlation Between the Trajectory of the Center of Pressure and Thermography of Cancer Patients Undergoing Chemotherapy.

OBJECTIVE: The purpose of this study was to correlate potential the stabilometric parameters of baro...

Precise pulmonary scanning and reducing medical radiation exposure by developing a clinically applicable intelligent CT system: Toward improving patient care.

BACKGROUND: Interstitial lung disease requires frequent re-examination, which directly causes excess...

Re: Comparison of Outcomes of Salvage Robot-Assisted Laparoscopic Prostatectomy for Post-Primary Radiation vs Focal Therapy.

Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.

Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and ...

Ontologies in radiation oncology.

Ontologies are a formal, computer-compatible method for representing scientific knowledge about a gi...

Triple-Negative Breast Cancer: A Review of Conventional and Advanced Therapeutic Strategies.

Triple-negative breast cancer (TNBC) cells are deficient in estrogen, progesterone and ERBB2 recepto...

Multicontext multitask learning networks for mass detection in mammogram.

PURPOSE: In this paper, for the purpose of accurate and efficient mass detection, we propose a new d...

Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning.

Early detection of breast cancer and its correct stage determination are important for prognosis and...

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods.

Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment ...

The Impact of Artificial Intelligence and Machine Learning in Radiation Therapy: Considerations for Future Curriculum Enhancement.

Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many ...

Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.

The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optim...

Label-Free Leukemia Monitoring by Computer Vision.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of ...

Comparison of statistical machine learning models for rectal protocol compliance in prostate external beam radiation therapy.

PURPOSE: Limiting the dose to the rectum can be one of the most challenging aspects of creating a do...

Inconsistent Performance of Deep Learning Models on Mammogram Classification.

OBJECTIVES: Performance of recently developed deep learning models for image classification surpasse...

Machine Learning Algorithms for Predicting the Recurrence of Stage IV Colorectal Cancer After Tumor Resection.

The aim of this study is to explore the feasibility of using machine learning (ML) technology to pre...

A deep learning approach to radiation dose estimation.

Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather ...

Deep DoseNet: a deep neural network for accurate dosimetric transformation between different spatial resolutions and/or different dose calculation algorithms for precision radiation therapy.

The purpose of this work is to introduce a novel deep learning strategy to obtain highly accurate do...

User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions.

PURPOSE: Precision cancer medicine is dependent on accurate prediction of disease and treatment outc...

Artificial Intelligence and CT Image Reconstruction: Potential of a New Era in Radiation Dose Reduction.

Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them.

In radiation oncology, Machine Learning classification publications are typically related to two out...

Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Curr...