AIMC Topic: Breast Neoplasms

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An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome.

BMC bioinformatics
BACKGROUND: Predicting outcome of breast cancer is important for selecting appropriate treatments and prolonging the survival periods of patients. Recently, different deep learning-based methods have been carefully designed for cancer outcome predict...

Clinical Integration of Artificial Intelligence for Breast Imaging.

Radiologic clinics of North America
This article describes an approach to planning and implementing artificial intelligence products in a breast screening service. It highlights the importance of an in-depth understanding of the end-to-end workflow and effective project planning by a m...

An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population: A prospective cohort and modeling study.

Chinese medical journal
BACKGROUND: Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk amon...

A deep learning based holistic diagnosis system for immunohistochemistry interpretation and molecular subtyping.

Neoplasia (New York, N.Y.)
BACKGROUND: Breast cancer in different molecular subtypes, which is determined by the overexpression rates of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR), and Ki67, exhibit distinct symptom char...

Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program.

European radiology
OBJECTIVES: We aimed to evaluate the early-detection capabilities of AI in a screening program over its duration, with a specific focus on the detection of interval cancers, the early detection of cancers with the assistance of AI from prior visits, ...

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning.

Biochemical genetics
Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate th...

A journey from omics to clinicomics in solid cancers: Success stories and challenges.

Advances in protein chemistry and structural biology
The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading...