113 related articles for article (PubMed ID: 38719649)
1. Machine Learning-Based Prediction of Pathological Responses and Prognosis After Neoadjuvant Chemotherapy for Non-Small-Cell Lung Cancer: A Retrospective Study.
Jiang Z; Li Q; Ruan J; Li Y; Zhang D; Xu Y; Liao Y; Zhang X; Gao D; Li Z
Clin Lung Cancer; 2024 Jul; 25(5):468-478.e3. PubMed ID: 38719649
[TBL] [Abstract][Full Text] [Related]
2. A combined model using pre-treatment CT radiomics and clinicopathological features of non-small cell lung cancer to predict major pathological responses after neoadjuvant chemoimmunotherapy.
Wang F; Yang H; Chen W; Ruan L; Jiang T; Cheng L; Jiang H; Fang M
Curr Probl Cancer; 2024 Jun; 50():101098. PubMed ID: 38704949
[TBL] [Abstract][Full Text] [Related]
3. CT-based quantification of intratumoral heterogeneity for predicting pathologic complete response to neoadjuvant immunochemotherapy in non-small cell lung cancer.
Ye G; Wu G; Zhang C; Wang M; Liu H; Song E; Zhuang Y; Li K; Qi Y; Liao Y
Front Immunol; 2024; 15():1414954. PubMed ID: 38933281
[TBL] [Abstract][Full Text] [Related]
4. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer.
Li ZY; Wang XD; Li M; Liu XJ; Ye Z; Song B; Yuan F; Yuan Y; Xia CC; Zhang X; Li Q
World J Gastroenterol; 2020 May; 26(19):2388-2402. PubMed ID: 32476800
[TBL] [Abstract][Full Text] [Related]
5. [
Yang M; Li X; Cai C; Liu C; Ma M; Qu W; Zhong S; Zheng E; Zhu H; Jin F; Shi H
Eur Radiol; 2024 Jul; 34(7):4352-4363. PubMed ID: 38127071
[TBL] [Abstract][Full Text] [Related]
6. Computed tomography RECIST assessment of histopathologic response and prediction of survival in patients with resectable non-small-cell lung cancer after neoadjuvant chemotherapy.
William WN; Pataer A; Kalhor N; Correa AM; Rice DC; Wistuba II; Heymach J; Lee JJ; Kim ES; Munden R; Gold KA; Papadimitrakopoulou V; Swisher SG; Erasmus JJ;
J Thorac Oncol; 2013 Feb; 8(2):222-8. PubMed ID: 23287849
[TBL] [Abstract][Full Text] [Related]
7. Assessment of Intratumoral and Peritumoral Computed Tomography Radiomics for Predicting Pathological Complete Response to Neoadjuvant Chemoradiation in Patients With Esophageal Squamous Cell Carcinoma.
Hu Y; Xie C; Yang H; Ho JWK; Wen J; Han L; Chiu KWH; Fu J; Vardhanabhuti V
JAMA Netw Open; 2020 Sep; 3(9):e2015927. PubMed ID: 32910196
[TBL] [Abstract][Full Text] [Related]
8. CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction.
Vaidya P; Bera K; Gupta A; Wang X; Corredor G; Fu P; Beig N; Prasanna P; Patil PD; Velu PD; Rajiah P; Gilkeson R; Feldman MD; Choi H; Velcheti V; Madabhushi A
Lancet Digit Health; 2020 Mar; 2(3):e116-e128. PubMed ID: 33334576
[TBL] [Abstract][Full Text] [Related]
9. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
[TBL] [Abstract][Full Text] [Related]
10. Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.
Dercle L; Fronheiser M; Lu L; Du S; Hayes W; Leung DK; Roy A; Wilkerson J; Guo P; Fojo AT; Schwartz LH; Zhao B
Clin Cancer Res; 2020 May; 26(9):2151-2162. PubMed ID: 32198149
[TBL] [Abstract][Full Text] [Related]
11. Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer patients: use of MRI radiomics data from three regions with multiple machine learning algorithms.
Zheng G; Peng J; Shu Z; Jin H; Han L; Yuan Z; Qin X; Hou J; He X; Gong X
J Cancer Res Clin Oncol; 2024 Mar; 150(3):147. PubMed ID: 38512406
[TBL] [Abstract][Full Text] [Related]
12. Neoadjuvant chemotherapy with docetaxel-cisplatin in patients with stage III N2 non-small-cell lung cancer.
Liao WY; Chen JH; Wu M; Shih JY; Chen KY; Ho CC; Yang JC; Yu CJ
Clin Lung Cancer; 2013 Jul; 14(4):418-24. PubMed ID: 23291258
[TBL] [Abstract][Full Text] [Related]
13. Prediction of neoadjuvant chemotherapy pathological complete response for breast cancer based on radiomics nomogram of intratumoral and derived tissue.
Zheng G; Hou J; Shu Z; Peng J; Han L; Yuan Z; He X; Gong X
BMC Med Imaging; 2024 Jan; 24(1):22. PubMed ID: 38245712
[TBL] [Abstract][Full Text] [Related]
14. Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using a deep learning (DL) method.
Qu YH; Zhu HT; Cao K; Li XT; Ye M; Sun YS
Thorac Cancer; 2020 Mar; 11(3):651-658. PubMed ID: 31944571
[TBL] [Abstract][Full Text] [Related]
15. Pathologic complete response to preoperative chemotherapy predicts cure in early-stage non-small-cell lung cancer: combined analysis of two IFCT randomized trials.
Mouillet G; Monnet E; Milleron B; Puyraveau M; Quoix E; David P; Ducoloné A; Molinier O; Zalcman G; Depierre A; Westeel V;
J Thorac Oncol; 2012 May; 7(5):841-9. PubMed ID: 22722786
[TBL] [Abstract][Full Text] [Related]
16. Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma.
Zhang XF; Wu HY; Liang XW; Chen JL; Li J; Zhang S; Liu Z
BMC Womens Health; 2024 Mar; 24(1):182. PubMed ID: 38504245
[TBL] [Abstract][Full Text] [Related]
17. Combination of computed tomography imaging-based radiomics and clinicopathological characteristics for predicting the clinical benefits of immune checkpoint inhibitors in lung cancer.
Yang B; Zhou L; Zhong J; Lv T; Li A; Ma L; Zhong J; Yin S; Huang L; Zhou C; Li X; Ge YQ; Tao X; Zhang L; Son Y; Lu G
Respir Res; 2021 Jun; 22(1):189. PubMed ID: 34183009
[TBL] [Abstract][Full Text] [Related]
18. Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.
Song J; Wang L; Ng NN; Zhao M; Shi J; Wu N; Li W; Liu Z; Yeom KW; Tian J
JAMA Netw Open; 2020 Dec; 3(12):e2030442. PubMed ID: 33331920
[TBL] [Abstract][Full Text] [Related]
19. Towards a survival risk prediction model for metastatic NSCLC patients on durvalumab using whole-lung CT radiomics.
Patwardhan KA; RaviPrakash H; Nikolaou N; Gonzalez-García I; Salazar JD; Metcalfe P; Reischl J
Front Immunol; 2024; 15():1383644. PubMed ID: 38915397
[TBL] [Abstract][Full Text] [Related]
20. Clinical outcomes associated with neoadjuvant therapy for the treatment of resectable non-small cell lung cancer in real-world practice.
Huang X; Pang G; Mao Z; Li B; Teng Z; Yang Y; Qiu Z; Chen X; Wang P
Clin Respir J; 2024 May; 18(5):e13761. PubMed ID: 38693705
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]