146 related articles for article (PubMed ID: 38503827)
1. Investigation of deep learning model for predicting immune checkpoint inhibitor treatment efficacy on contrast-enhanced computed tomography images of hepatocellular carcinoma.
Nakao Y; Nishihara T; Sasaki R; Fukushima M; Miuma S; Miyaaki H; Akazawa Y; Nakao K
Sci Rep; 2024 Mar; 14(1):6576. PubMed ID: 38503827
[TBL] [Abstract][Full Text] [Related]
2. Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging.
Peng J; Kang S; Ning Z; Deng H; Shen J; Xu Y; Zhang J; Zhao W; Li X; Gong W; Huang J; Liu L
Eur Radiol; 2020 Jan; 30(1):413-424. PubMed ID: 31332558
[TBL] [Abstract][Full Text] [Related]
3. Development of an AI system for accurately diagnose hepatocellular carcinoma from computed tomography imaging data.
Wang M; Fu F; Zheng B; Bai Y; Wu Q; Wu J; Sun L; Liu Q; Liu M; Yang Y; Shen H; Kong D; Ma X; You P; Li X; Tian F
Br J Cancer; 2021 Oct; 125(8):1111-1121. PubMed ID: 34365472
[TBL] [Abstract][Full Text] [Related]
4. Contrast-enhanced CT parameters predict short-term tumor response in patients with hepatocellular carcinoma who received sequential combined anti-angiogenesis and immune checkpoint inhibitor treatment.
Feng Y; Zhang H; Ren Q; Li C; Liu S; Zheng C; Xia X
Eur J Radiol; 2023 May; 162():110784. PubMed ID: 36958125
[TBL] [Abstract][Full Text] [Related]
5. Diagnostic Value of Quantitative Perfusion Computed Tomography Technique in the Assessment of Tumor Response to Sorafenib in Patients With Advanced Hepatocellular Carcinoma.
Ippolito D; Querques G; Pecorelli A; Talei Franzesi C; Okolicsanyi S; Strazzabosco M; Sironi S
J Comput Assist Tomogr; 2019; 43(2):206-213. PubMed ID: 30407241
[TBL] [Abstract][Full Text] [Related]
6. Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals.
Liu SC; Lai J; Huang JY; Cho CF; Lee PH; Lu MH; Yeh CC; Yu J; Lin WC
Cancer Imaging; 2021 Oct; 21(1):56. PubMed ID: 34627393
[TBL] [Abstract][Full Text] [Related]
7. Biochemical predictors of response to immune checkpoint inhibitors in unresectable hepatocellular carcinoma.
Rizzo A; Brandi G
Cancer Treat Res Commun; 2021; 27():100328. PubMed ID: 33549983
[TBL] [Abstract][Full Text] [Related]
8. Monitoring response to antiangiogenic treatment and predicting outcomes in advanced hepatocellular carcinoma using image biomarkers, CT perfusion, tumor density, and tumor size (RECIST).
Jiang T; Kambadakone A; Kulkarni NM; Zhu AX; Sahani DV
Invest Radiol; 2012 Jan; 47(1):11-7. PubMed ID: 21512396
[TBL] [Abstract][Full Text] [Related]
9. Evaluation of sorafenib for hepatocellular carcinoma by contrast-enhanced ultrasonography: a pilot study.
Shiozawa K; Watanabe M; Kikuchi Y; Kudo T; Maruyama K; Sumino Y
World J Gastroenterol; 2012 Oct; 18(40):5753-8. PubMed ID: 23155317
[TBL] [Abstract][Full Text] [Related]
10. Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.
Joo MW; Ko T; Kim MS; Lee YS; Shin SH; Chung YG; Lee HK
Clin Orthop Relat Res; 2023 Nov; 481(11):2247-2256. PubMed ID: 37615504
[TBL] [Abstract][Full Text] [Related]
11. Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.
Xu Z; An C; Shi F; Ren H; Li Y; Chen S; Dou J; Wang Y; Yan S; Lu J; Chen H
Eur Radiol; 2023 Dec; 33(12):9038-9051. PubMed ID: 37498380
[TBL] [Abstract][Full Text] [Related]
12. CT images-based 3D convolutional neural network to predict early recurrence of solitary hepatocellular carcinoma after radical hepatectomy.
Cui H; Wang KY; Li WY; Zhu HB; Xiao LS; Liu L
Diagn Interv Radiol; 2022 Nov; 28(6):524-531. PubMed ID: 36287132
[TBL] [Abstract][Full Text] [Related]
13. Irreversible electroporation of hepatocellular carcinoma: preliminary report on the diagnostic accuracy of magnetic resonance, computer tomography, and contrast-enhanced ultrasound in evaluation of the ablated area.
Granata V; de Lutio di Castelguidone E; Fusco R; Catalano O; Piccirillo M; Palaia R; Izzo F; Gallipoli AD; Petrillo A
Radiol Med; 2016 Feb; 121(2):122-31. PubMed ID: 26345332
[TBL] [Abstract][Full Text] [Related]
14. An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer.
He T; Fong JN; Moore LW; Ezeana CF; Victor D; Divatia M; Vasquez M; Ghobrial RM; Wong STC
Comput Med Imaging Graph; 2021 Apr; 89():101894. PubMed ID: 33725579
[TBL] [Abstract][Full Text] [Related]
15. Classification of metastatic hepatic carcinoma and hepatocellular carcinoma lesions using contrast-enhanced CT based on EI-CNNet.
Wang X; Li N; Yin X; Xing L; Zheng Y
Med Phys; 2023 Sep; 50(9):5630-5642. PubMed ID: 36869656
[TBL] [Abstract][Full Text] [Related]
16. Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images.
Tian P; He B; Mu W; Liu K; Liu L; Zeng H; Liu Y; Jiang L; Zhou P; Huang Z; Dong D; Li W
Theranostics; 2021; 11(5):2098-2107. PubMed ID: 33500713
[No Abstract] [Full Text] [Related]
17. Computer-aided diagnosis of cirrhosis and hepatocellular carcinoma using multi-phase abdomen CT.
Nayak A; Baidya Kayal E; Arya M; Culli J; Krishan S; Agarwal S; Mehndiratta A
Int J Comput Assist Radiol Surg; 2019 Aug; 14(8):1341-1352. PubMed ID: 31062266
[TBL] [Abstract][Full Text] [Related]
18. Improving radiomics reproducibility using deep learning-based image conversion of CT reconstruction algorithms in hepatocellular carcinoma patients.
Lee H; Chang W; Kim HY; Sung P; Cho J; Lee YJ; Kim YH
Eur Radiol; 2024 Mar; 34(3):2036-2047. PubMed ID: 37656175
[TBL] [Abstract][Full Text] [Related]
19. MRI-Based Radiomics and Deep Learning in Biological Characteristics and Prognosis of Hepatocellular Carcinoma: Opportunities and Challenges.
Xia T; Zhao B; Li B; Lei Y; Song Y; Wang Y; Tang T; Ju S
J Magn Reson Imaging; 2024 Mar; 59(3):767-783. PubMed ID: 37647155
[TBL] [Abstract][Full Text] [Related]
20. Low dose of contrast agent and low radiation liver computed tomography with deep-learning-based contrast boosting model in participants at high-risk for hepatocellular carcinoma: prospective, randomized, double-blind study.
Kang HJ; Lee JM; Ahn C; Bae JS; Han S; Kim SW; Yoon JH; Han JK
Eur Radiol; 2023 May; 33(5):3660-3670. PubMed ID: 36934202
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
