Asian Pacific journal of cancer prevention : APJCP
Nov 1, 2021
OBJECTIVE: Early prediction of breast cancer is one of the most essential fields of medicine. Many studies have introduced prediction approaches to facilitate the early prediction and estimate the future occurrence based on mammography periodic tests...
In healthcare, artificial intelligence (AI) technologies have the potential to create significant value by improving time-sensitive outcomes while lowering error rates for each patient. Diagnostic images, clinical notes, and reports are increasingly ...
Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis for breast MRI, but ultrafast images, T2-weighted images, and diffusi...
Masses are one of the early signs of breast cancer, and the survival rate of women suffering from breast cancer can be improved if masses can be correctly identified as benign or malignant. However, their classification is challenging due to the simi...
Computational and mathematical methods in medicine
Oct 26, 2021
Diagnosis of different breast cancer stages using histopathology whole slide images (WSI) is the gold standard in determining the grade of tissue metastasis. Computer-aided diagnosis (CAD) assists medical experts as a second opinion tool in early det...
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
Oct 25, 2021
BACKGROUND: Disparities in the stage at diagnosis for breast cancer have been independently associated with various contextual characteristics. Understanding which combinations of these characteristics indicate highest risk, and where they are locate...
Early diagnosis of tumor plays an important role in the improvement of treatment and survival rate of patients. However, breast tumors are difficult to be diagnosed by invasive examination, so medical imaging has become the most intuitive auxiliary m...
Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often...
Background Advances in computer processing and improvements in data availability have led to the development of machine learning (ML) techniques for mammographic imaging. Purpose To evaluate the reported performance of stand-alone ML applications for...
OBJECTIVE: To study the impact of artificial intelligence (AI) on the performance of mammogram with regard to the classification of the detected breast lesions in correlation to ultrasound-aided mammograms.