Jiao Li
Sun Yat-sen University
9 Papers
Jiao Li is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Medicine & Mammography. The author has an hindex of 3, co-authored 4 publications.
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Papers
Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms.
TL;DR: The calcification was characterized by descriptors obtained from deep learning and handcrafted descriptors, which achieved a classification precision of 89.32% and sensitivity of 86.89% using the filtered deep features, which is the best performance among all the feature sets.
An Online Mammography Database with Biopsy Confirmed Types
Hongmin Cai,Jinhua Wang,Tingting Dan,Jiao Li,Zhihao Fan,Weiting Yi,Chunyan Cui,Xinhua Jiang,Li Li +8 more
TL;DR: Wang et al. as discussed by the authors built a database containing two online breast mammographies, which are used to enrich the diversity of mammography data and promote the development of relevant fields.
Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer.
Jiao Li,Weimei Ma,Jiang Xinhua,Chunyan Cui,Hongli Wang,Jiewen Chen,Runcong Nie,Yaopan Wu,Li Li +8 more
TL;DR: The nomograms could predict the extent of ALN metastasis and facilitate decision-making preoperatively and were validated to develop and validate nomogram models using noninvasive imaging parameters with related clinical variables.
Prognostic value of quantitative cervical nodal necrosis burden on MRI in nasopharyngeal carcinoma and its role as a stratification marker for induction chemotherapy
TL;DR: Assessment of the prognostic value of quantitative cervical nodal necrosis burden in N staging risk stratification in patients with nasopharyngeal carcinoma found multiple CNNs might be a potential marker for stratifying patients who would benefit from induction chemotherapy.
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Assessment of Cone-Beam Breast Computed Tomography for Predicting Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Prospective Study
Shen Chen,Sheng Li,Ni He,Jieting Chen,Sheng-Guang Pei,Jiao Li,Yao Pan Wu,Pei-Qiang Cai +7 more
TL;DR: Assessment of the imaging features of cone-beam breast computed tomography for predicting the pathologic response of breast cancer after neoadjuvant chemotherapy found the late-treatment parameters showed significant value with a predictive model.
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