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Correlated and individual feature learning with contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma.

, , , , , , , , , and . Pattern Recognit., (October 2023)

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Super-Resolution and Self-Attention with Generative Adversarial Network for Improving Malignancy Characterization of Hepatocellular Carcinoma., , , , , and . ISBI, page 1556-1560. IEEE, (2020)Application of patient-reported outcomes in clinical evaluation of acupuncture for cervical spondylosis with artificial neural network., , , , , and . BIBM, page 271-276. IEEE Computer Society, (2013)Discrepancy Steered Conditional Adversarial Network For Deep Feature Based Malignancy Characterization of Hepatocellular Carcinoma., , , , , and . ICIP, page 1342-1345. IEEE, (2019)Research on PRO scale of acupuncture for cervical spondylosis with multidimensional item response theory., , , , and . ICMLC, page 857-862. IEEE, (2016)Automatic identification peaks in chromatographic fingerprints based on fuzzy matching., , , and . FSKD, page 292-296. IEEE, (2012)Correlated and individual feature learning with contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma., , , , , , , , , and . Pattern Recognit., (October 2023)Deriving mutual modes from HPLC fingerprints of traditional Chinese medicine with non-negative matrix factorization., , , , , and . BIBM, page 265-270. IEEE Computer Society, (2013)Improving the malignancy characterization of hepatocellular carcinoma using deeply supervised cross modal transfer learning for non-enhanced MR., , , , , , , , and . EMBC, page 853-856. IEEE, (2019)A clinical outcome evaluation model with local sample selection: A study on efficacy of acupuncture for cervical spondylosis., , , , , , and . BIBM Workshops, page 829-833. IEEE Computer Society, (2011)Application of patient-reported outcomes in clinical evaluation model of acupuncture for cervical spondylosis with SEM and ANNs., , , , , , and . ICMLC, page 825-831. IEEE, (2016)