Deep learning in image-based breast and cervical cancer detection: a systematic review and meta-analysis
P Xue, J Wang, D Qin, H Yan, Y Qu, S Seery… - NPJ digital …, 2022 - nature.com
Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we
conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) …
conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) …
BI-RADS category prediction from mammography images and mammography radiology reports using deep learning: A systematic review
Women's health and mortality are significantly threatened by breast cancer, underscoring
the importance of timely detection and treatment. Mammograms are an extremely useful and …
the importance of timely detection and treatment. Mammograms are an extremely useful and …
Fusion-based tensor radiomics using reproducible features: application to survival prediction in head and neck cancer
Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …
Radiomics in breast MRI: Current progress toward clinical application in the era of artificial intelligence
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 …
cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis …
Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application
Y Meng, Y Yang, M Hu, Z Zhang, X Zhou - Seminars in Cancer Biology, 2023 - Elsevier
Radiomics is the extraction of predefined mathematic features from medical images for
predicting variables of clinical interest. Recent research has demonstrated that radiomics …
predicting variables of clinical interest. Recent research has demonstrated that radiomics …
Breast cancer, screening and diagnostic tools: All you need to know
D Barba, A León-Sosa, P Lugo, D Suquillo… - Critical reviews in …, 2021 - Elsevier
Breast cancer is one of the most frequent malignancies among women worldwide. Methods
for screening and diagnosis allow health care professionals to provide personalized …
for screening and diagnosis allow health care professionals to provide personalized …
Combining deep learning and handcrafted radiomics for classification of suspicious lesions on contrast-enhanced mammograms
Background Handcrafted radiomics and deep learning (DL) models individually achieve
good performance in lesion classification (benign vs malignant) on contrast-enhanced …
good performance in lesion classification (benign vs malignant) on contrast-enhanced …
Defining precancer: a grand challenge for the cancer community
The term 'precancer'typically refers to an early stage of neoplastic development that is
distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting …
distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting …
Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy
ZHE Zhang, X Wei - Seminars in Cancer Biology, 2023 - Elsevier
The rapid development of artificial intelligence (AI) technologies in the context of the vast
amount of collectable data obtained from high-throughput sequencing has led to an …
amount of collectable data obtained from high-throughput sequencing has led to an …
hist2RNA: An Efficient Deep Learning Architecture to Predict Gene Expression from Breast Cancer Histopathology Images
Simple Summary Breast cancer diagnosis and treatment can be improved by understanding
the specific genetic makeup of a patient's tumour. Currently, this genetic information is …
the specific genetic makeup of a patient's tumour. Currently, this genetic information is …