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9 in total

Review 1. The application of artificial intelligence and radiomics in lung cancer.

Authors: Yaojie Zhou; Xiuyuan Xu; Lujia Song; Chengdi Wang; Jixiang Guo; Zhang Yi; Weimin Li
Journal: Precis Clin Med Date: 2020-08-24

2. Mining Prognosis Index of Brain Metastases Using Artificial Intelligence.

Authors: Shigao Huang; Jie Yang; Simon Fong; Qi Zhao
Journal: Cancers (Basel) Date: 2019-08-09 Impact factor: 6.639

3. Predicting prognosis of endometrioid endometrial adenocarcinoma on the basis of gene expression and clinical features using Random Forest.

Authors: Fufen Yin; Xingyang Shao; Lijun Zhao; Xiaoping Li; Jingyi Zhou; Yuan Cheng; Xiangjun He; Shu Lei; Jiangeng Li; Jianliu Wang
Journal: Oncol Lett Date: 2019-06-20 Impact factor: 2.967

4. Four transcription profile-based models identify novel prognostic signatures in oesophageal cancer.

Authors: Tongyan Liu; Panqi Fang; Chencheng Han; Zhifei Ma; Weizhang Xu; Wenjia Xia; Jingwen Hu; Youtao Xu; Lin Xu; Rong Yin; Siwei Wang; Qin Zhang
Journal: J Cell Mol Med Date: 2019-11-19 Impact factor: 5.310

Review 5. Combining Molecular, Imaging, and Clinical Data Analysis for Predicting Cancer Prognosis.

Authors: Barbara Lobato-Delgado; Blanca Priego-Torres; Daniel Sanchez-Morillo
Journal: Cancers (Basel) Date: 2022-06-30 Impact factor: 6.575

Review 6. Machine Learning for Endometrial Cancer Prediction and Prognostication.

Authors: Vipul Bhardwaj; Arundhiti Sharma; Snijesh Valiya Parambath; Ijaz Gul; Xi Zhang; Peter E Lobie; Peiwu Qin; Vijay Pandey
Journal: Front Oncol Date: 2022-07-27 Impact factor: 5.738

7. Identification and Validation of Autophagy-Related Gene Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer.

Authors: Jinqun Jiang; HongYan Xu; YiHao Wang; Hai Lu
Journal: J Oncol Date: 2021-06-25 Impact factor: 4.375

Review 8. Reviewing the Utility of EUS FNA to Advance Precision Medicine in Pancreatic Cancer.

Authors: William Berry; Joanne Lundy; Daniel Croagh; Brendan J Jenkins
Journal: Cancers (Basel) Date: 2018-01-27 Impact factor: 6.639

9. Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up.

Authors: Congxin Dai; Yanghua Fan; Yichao Li; Xinjie Bao; Yansheng Li; Mingliang Su; Yong Yao; Kan Deng; Bing Xing; Feng Feng; Ming Feng; Renzhi Wang
Journal: Front Endocrinol (Lausanne) Date: 2020-09-16 Impact factor: 5.555

9 in total