115 related articles for article (PubMed ID: 38540086)
1. Machine Learning and Texture Analysis of [
Hakkak Moghadam Torbati A; Pellegrino S; Fonti R; Morra R; De Placido S; Del Vecchio S
Biomedicines; 2024 Feb; 12(3):. PubMed ID: 38540086
[TBL] [Abstract][Full Text] [Related]
2. The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [
Nakajo M; Kawaji K; Nagano H; Jinguji M; Mukai A; Kawabata H; Tani A; Hirahara D; Yamashita M; Yoshiura T
Mol Imaging Biol; 2023 Apr; 25(2):303-313. PubMed ID: 35864282
[TBL] [Abstract][Full Text] [Related]
3. An [
Meng N; Feng P; Yu X; Wu Y; Fu F; Li Z; Luo Y; Tan H; Yuan J; Yang Y; Wang Z; Wang M
Eur Radiol; 2024 Jan; 34(1):318-329. PubMed ID: 37530809
[TBL] [Abstract][Full Text] [Related]
4. Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [
Gómez OV; Herraiz JL; Udías JM; Haug A; Papp L; Cioni D; Neri E
Cancers (Basel); 2022 Jun; 14(12):. PubMed ID: 35740588
[TBL] [Abstract][Full Text] [Related]
5. Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Using Convolutional Neural Network of Tumor Center
Kim J; Jeong SY; Kim BC; Byun BH; Lim I; Kong CB; Song WS; Lim SM; Woo SK
Diagnostics (Basel); 2021 Oct; 11(11):. PubMed ID: 34829324
[TBL] [Abstract][Full Text] [Related]
6. Machine learning approach using
Nakajo M; Hirahara D; Jinguji M; Ojima S; Hirahara M; Tani A; Takumi K; Kamimura K; Ohishi M; Yoshiura T
Jpn J Radiol; 2024 Mar; ():. PubMed ID: 38491333
[TBL] [Abstract][Full Text] [Related]
7. Machine learning based evaluation of clinical and pretreatment
Nakajo M; Jinguji M; Tani A; Yano E; Hoo CK; Hirahara D; Togami S; Kobayashi H; Yoshiura T
Abdom Radiol (NY); 2022 Feb; 47(2):838-847. PubMed ID: 34821963
[TBL] [Abstract][Full Text] [Related]
8. Use of radiomics based on
Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
[TBL] [Abstract][Full Text] [Related]
9. Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer.
Liao S; Penney BC; Wroblewski K; Zhang H; Simon CA; Kampalath R; Shih MC; Shimada N; Chen S; Salgia R; Appelbaum DE; Suzuki K; Chen CT; Pu Y
Eur J Nucl Med Mol Imaging; 2012 Jan; 39(1):27-38. PubMed ID: 21946983
[TBL] [Abstract][Full Text] [Related]
10. A machine learning tool to improve prediction of mediastinal lymph node metastases in non-small cell lung cancer using routinely obtainable [
Rogasch JMM; Michaels L; Baumgärtner GL; Frost N; Rückert JC; Neudecker J; Ochsenreither S; Gerhold M; Schmidt B; Schneider P; Amthauer H; Furth C; Penzkofer T
Eur J Nucl Med Mol Imaging; 2023 Jun; 50(7):2140-2151. PubMed ID: 36820890
[TBL] [Abstract][Full Text] [Related]
11. Developing a primary tumor and lymph node 18F-FDG PET/CT-clinical (TLPC) model to predict lymph node metastasis of resectable T2-4 NSCLC.
Wang M; Liu L; Dai Q; Jin M; Huang G
J Cancer Res Clin Oncol; 2023 Jan; 149(1):247-261. PubMed ID: 36565319
[TBL] [Abstract][Full Text] [Related]
12. Texture Analysis of
Fan X; Zhang H; Yin Y; Zhang J; Yang M; Qin S; Zhang X; Yu F
Front Med (Lausanne); 2020; 7():605746. PubMed ID: 33521018
[No Abstract] [Full Text] [Related]
13. Graph Neural Network Model for Prediction of Non-Small Cell Lung Cancer Lymph Node Metastasis Using Protein-Protein Interaction Network and
Ju H; Kim K; Kim BI; Woo SK
Int J Mol Sci; 2024 Jan; 25(2):. PubMed ID: 38255770
[TBL] [Abstract][Full Text] [Related]
14. Prediction of Chemotherapy Response of Osteosarcoma Using Baseline
Jeong SY; Kim W; Byun BH; Kong CB; Song WS; Lim I; Lim SM; Woo SK
Contrast Media Mol Imaging; 2019; 2019():3515080. PubMed ID: 31427908
[TBL] [Abstract][Full Text] [Related]
15. Preoperative prediction of regional lymph node metastasis of colorectal cancer based on
He J; Wang Q; Zhang Y; Wu H; Zhou Y; Zhao S
Ann Nucl Med; 2021 May; 35(5):617-627. PubMed ID: 33738763
[TBL] [Abstract][Full Text] [Related]
16. 18F-FDG PET/CT and circulating tumor cells in treatment-naive patients with non-small-cell lung cancer.
Zhang F; Wu X; Zhu J; Huang Y; Song X; Jiang L
Eur J Nucl Med Mol Imaging; 2021 Sep; 48(10):3250-3259. PubMed ID: 33630146
[TBL] [Abstract][Full Text] [Related]
17. Value of volumetric and textural analysis in predicting the treatment response in patients with locally advanced rectal cancer.
Karahan Şen NP; Aksu A; Kaya GÇ
Ann Nucl Med; 2020 Dec; 34(12):960-967. PubMed ID: 32951129
[TBL] [Abstract][Full Text] [Related]
18. Improving the Classification of PCNSL and Brain Metastases by Developing a Machine Learning Model Based on
Cui C; Yao X; Xu L; Chao Y; Hu Y; Zhao S; Hu Y; Zhang J
J Pers Med; 2023 Mar; 13(3):. PubMed ID: 36983721
[No Abstract] [Full Text] [Related]
19. Radiomic Analysis of Positron-Emission Tomography and Computed Tomography Images to Differentiate between Multiple Myeloma and Skeletal Metastases.
Mannam P; Murali A; Gokulakrishnan P; Venkatachalapathy E; Venkata Sai PM
Indian J Nucl Med; 2022; 37(3):217-226. PubMed ID: 36686312
[TBL] [Abstract][Full Text] [Related]
20. Prediction of the treatment outcome using machine learning with FDG-PET image-based multiparametric approach in patients with oral cavity squamous cell carcinoma.
Fujima N; Andreu-Arasa VC; Meibom SK; Mercier GA; Salama AR; Truong MT; Sakai O
Clin Radiol; 2021 Sep; 76(9):711.e1-711.e7. PubMed ID: 33934877
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
