Total 51건 1 페이지
의료진 목록
번호 제목 글쓴이 조회 날짜
51
Comprehensive gene expression analysis for exploring the association between glucose metabolism and differentiation of thyroid cancer.
NMSNUH 33 05-20
50
18 F-FDG uptake in denervated muscles of patients with peripheral nerve injury.
NMSNUH 25 05-20
49
Association of metabolic and genetic heterogeneity in head and neck squamous cell carcinoma with prognostic implications: integration of FDG PET and genomic analysis.
NMSNUH 27 05-20
48
Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.
NMSNUH 39 05-20
47
Effect of Sevoflurane Postconditioning on the Incidence of Symptomatic Cerebral Hyperperfusion After Revascularization Surgery in Adult Patients with Moyamoya Disease.
NMSNUH 26 05-20
46
Amyloid PET Quantification Via End-to-End Training of a Deep Learning.
NMSNUH 31 05-20
45
Deep learning only by normal brain PET identify unheralded brain anomalies.
NMSNUH 24 05-20
44
18F-FDG positron emission tomography as a novel diagnostic tool for peripheral nerve injury.
NMSNUH 30 05-20
43
Radiomics in Oncological PET/CT: a Methodological Overview.
NMSNUH 33 05-20
42
Tumor Metabolic Features Identified by 18F-FDG PET Correlate with Gene Networks of Immune Cell Microenvironment in Head and Neck Cancer.
NMSNUH 29 05-20
41
Generation of Structural MR Images from Amyloid PET: Application to MR-Less Quantification.
NMSNUH 39 05-20
40
Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging.
NMSNUH 37 05-20
39
Immune landscape of papillary thyroid cancer and immunotherapeutic implications.
NMSNUH 29 05-20
38
Integrative analysis of imaging and transcriptomic data of the immune landscape associated with tumor metabolism in lung adenocarcinoma: Clinical and prognostic implications.
NMSNUH 28 05-20
37
Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder.
NMSNUH 44 05-20
36
Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions.
NMSNUH 36 05-20
35
A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning.
NMSNUH 40 05-20
34
A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning.
NMSNUH 26 05-20
33
Application of Quantitative Indexes of FDG PET to Treatment Response Evaluation in Indolent Lymphoma.
NMSNUH 35 05-20
32
Pan-cancer analysis of tumor metabolic landscape associated with genomic alterations.
NMSNUH 40 05-20

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