236 related articles for article (PubMed ID: 35871390)
1. Using machine learning for mortality prediction and risk stratification in atezolizumab-treated cancer patients: Integrative analysis of eight clinical trials.
Wu Y; Zhu W; Wang J; Liu L; Zhang W; Wang Y; Shi J; Xia J; Gu Y; Qian Q; Hong Y
Cancer Med; 2023 Feb; 12(3):3744-3757. PubMed ID: 35871390
[TBL] [Abstract][Full Text] [Related]
2. Application of machine learning model in predicting the likelihood of blood transfusion after hip fracture surgery.
Chen X; Pan J; Li Y; Tang R
Aging Clin Exp Res; 2023 Nov; 35(11):2643-2656. PubMed ID: 37733228
[TBL] [Abstract][Full Text] [Related]
3. Machine learning approaches for prediction of early death among lung cancer patients with bone metastases using routine clinical characteristics: An analysis of 19,887 patients.
Cui Y; Shi X; Wang S; Qin Y; Wang B; Che X; Lei M
Front Public Health; 2022; 10():1019168. PubMed ID: 36276398
[TBL] [Abstract][Full Text] [Related]
4. Atezolizumab in combination with carboplatin plus nab-paclitaxel chemotherapy compared with chemotherapy alone as first-line treatment for metastatic non-squamous non-small-cell lung cancer (IMpower130): a multicentre, randomised, open-label, phase 3 trial.
West H; McCleod M; Hussein M; Morabito A; Rittmeyer A; Conter HJ; Kopp HG; Daniel D; McCune S; Mekhail T; Zer A; Reinmuth N; Sadiq A; Sandler A; Lin W; Ochi Lohmann T; Archer V; Wang L; Kowanetz M; Cappuzzo F
Lancet Oncol; 2019 Jul; 20(7):924-937. PubMed ID: 31122901
[TBL] [Abstract][Full Text] [Related]
5. Primary results from TAIL: a global single-arm safety study of atezolizumab monotherapy in a diverse population of patients with previously treated advanced non-small cell lung cancer.
Ardizzoni A; Azevedo S; Rubio-Viqueira B; Rodríguez-Abreu D; Alatorre-Alexander J; Smit HJM; Yu J; Syrigos K; Trunzer K; Patel H; Tolson J; Cardona A; Perez-Moreno PD; Newsom-Davis T
J Immunother Cancer; 2021 Mar; 9(3):. PubMed ID: 33737339
[TBL] [Abstract][Full Text] [Related]
6. Development and validation of a web-based artificial intelligence prediction model to assess massive intraoperative blood loss for metastatic spinal disease using machine learning techniques.
Shi X; Cui Y; Wang S; Pan Y; Wang B; Lei M
Spine J; 2024 Jan; 24(1):146-160. PubMed ID: 37704048
[TBL] [Abstract][Full Text] [Related]
7. Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods.
Zhou JG; Wong AH; Wang H; Tan F; Chen X; Jin SH; He SS; Shen G; Wang YJ; Frey B; Fietkau R; Hecht M; Ma H; Gaipl US
Front Immunol; 2022; 13():862752. PubMed ID: 35844547
[TBL] [Abstract][Full Text] [Related]
8. Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer.
Parikh RB; Manz C; Chivers C; Regli SH; Braun J; Draugelis ME; Schuchter LM; Shulman LN; Navathe AS; Patel MS; O'Connor NR
JAMA Netw Open; 2019 Oct; 2(10):e1915997. PubMed ID: 31651973
[TBL] [Abstract][Full Text] [Related]
9. Single or combined immune checkpoint inhibitors compared to first-line platinum-based chemotherapy with or without bevacizumab for people with advanced non-small cell lung cancer.
Ferrara R; Imbimbo M; Malouf R; Paget-Bailly S; Calais F; Marchal C; Westeel V
Cochrane Database Syst Rev; 2020 Dec; 12(12):CD013257. PubMed ID: 33316104
[TBL] [Abstract][Full Text] [Related]
10. Primary Results from SAUL, a Multinational Single-arm Safety Study of Atezolizumab Therapy for Locally Advanced or Metastatic Urothelial or Nonurothelial Carcinoma of the Urinary Tract.
Sternberg CN; Loriot Y; James N; Choy E; Castellano D; Lopez-Rios F; Banna GL; De Giorgi U; Masini C; Bamias A; Garcia Del Muro X; Duran I; Powles T; Gamulin M; Zengerling F; Geczi L; Gedye C; de Ducla S; Fear S; Merseburger AS
Eur Urol; 2019 Jul; 76(1):73-81. PubMed ID: 30910346
[TBL] [Abstract][Full Text] [Related]
11. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
[TBL] [Abstract][Full Text] [Related]
12. Machine learning-based risk prediction of malignant arrhythmia in hospitalized patients with heart failure.
Wang Q; Li B; Chen K; Yu F; Su H; Hu K; Liu Z; Wu G; Yan J; Su G
ESC Heart Fail; 2021 Dec; 8(6):5363-5371. PubMed ID: 34585531
[TBL] [Abstract][Full Text] [Related]
13. Atezolizumab (MPDL3280A) Monotherapy for Patients With Metastatic Urothelial Cancer: Long-term Outcomes From a Phase 1 Study.
Petrylak DP; Powles T; Bellmunt J; Braiteh F; Loriot Y; Morales-Barrera R; Burris HA; Kim JW; Ding B; Kaiser C; Fassò M; O'Hear C; Vogelzang NJ
JAMA Oncol; 2018 Apr; 4(4):537-544. PubMed ID: 29423515
[TBL] [Abstract][Full Text] [Related]
14. Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicentre, open-label, phase 2 randomised controlled trial.
Fehrenbacher L; Spira A; Ballinger M; Kowanetz M; Vansteenkiste J; Mazieres J; Park K; Smith D; Artal-Cortes A; Lewanski C; Braiteh F; Waterkamp D; He P; Zou W; Chen DS; Yi J; Sandler A; Rittmeyer A;
Lancet; 2016 Apr; 387(10030):1837-46. PubMed ID: 26970723
[TBL] [Abstract][Full Text] [Related]
15. Safety and Efficacy of Atezolizumab in Understudied Populations with Pretreated Urinary Tract Carcinoma: Subgroup Analyses of the SAUL Study in Real-World Practice.
Merseburger AS; Castellano D; Powles T; Loriot Y; Retz M; Voortman J; Huddart RA; Gedye C; Van Der Heijden MS; Gurney H; Ong M; de Ducla S; Pavlova J; Fear S; Sternberg CN
J Urol; 2021 Aug; 206(2):240-251. PubMed ID: 33835866
[TBL] [Abstract][Full Text] [Related]
16. Machine learning-based algorithms to predict severe psychological distress among cancer patients with spinal metastatic disease.
Gao L; Cao Y; Cao X; Shi X; Lei M; Su X; Liu Y
Spine J; 2023 Sep; 23(9):1255-1269. PubMed ID: 37182703
[TBL] [Abstract][Full Text] [Related]
17. Real-world efficacy of atezolizumab in non-small cell lung cancer: A multicenter cohort study focused on performance status and retreatment after failure of anti-PD-1 antibody.
Furuya N; Nishino M; Wakuda K; Ikeda S; Sato T; Ushio R; Tanzawa S; Sata M; Ito K
Thorac Cancer; 2021 Mar; 12(5):613-618. PubMed ID: 33448648
[TBL] [Abstract][Full Text] [Related]
18. A clinical variable-based nomogram could predict the survival for advanced NSCLC patients receiving second-line atezolizumab.
Shang X; Shi J; Wang X; Zhao C; Yu H; Wang H
Cancer Med; 2021 Sep; 10(18):6218-6226. PubMed ID: 34331414
[TBL] [Abstract][Full Text] [Related]
19. Comparison of Conventional Logistic Regression and Machine Learning Methods for Predicting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: A Multicentric Observational Cohort Study.
Hu P; Li Y; Liu Y; Guo G; Gao X; Su Z; Wang L; Deng G; Yang S; Qi Y; Xu Y; Ye L; Sun Q; Nie X; Sun Y; Li M; Zhang H; Chen Q
Front Aging Neurosci; 2022; 14():857521. PubMed ID: 35783143
[TBL] [Abstract][Full Text] [Related]
20. The prediction of in-hospital mortality in chronic kidney disease patients with coronary artery disease using machine learning models.
Ye Z; An S; Gao Y; Xie E; Zhao X; Guo Z; Li Y; Shen N; Ren J; Zheng J
Eur J Med Res; 2023 Jan; 28(1):33. PubMed ID: 36653875
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
