192 related articles for article (PubMed ID: 34193166)
1. Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.
Li X; Yang L; Yuan Z; Lou J; Fan Y; Shi A; Huang J; Zhao M; Wu Y
J Transl Med; 2021 Jun; 19(1):281. PubMed ID: 34193166
[TBL] [Abstract][Full Text] [Related]
2. Preoperative recurrence prediction in pancreatic ductal adenocarcinoma after radical resection using radiomics of diagnostic computed tomography.
Li X; Wan Y; Lou J; Xu L; Shi A; Yang L; Fan Y; Yang J; Huang J; Wu Y; Niu T
EClinicalMedicine; 2022 Jan; 43():101215. PubMed ID: 34927034
[TBL] [Abstract][Full Text] [Related]
3. Gene signature developed for predicting early relapse and survival in early-stage pancreatic cancer.
Huang L; Yuan X; Zhao L; Han Q; Yan H; Yuan J; Guan S; Xu X; Dai G; Wang J; Shi Y
BJS Open; 2023 May; 7(3):. PubMed ID: 37196196
[TBL] [Abstract][Full Text] [Related]
4. Development and validation of a nomogram to predict liver metastasis for pancreatic ductal adenocarcinoma after radical resection.
Tong J; Jiang W; Mao S; Wu S; Lu C
Front Oncol; 2022; 12():1040411. PubMed ID: 36479089
[TBL] [Abstract][Full Text] [Related]
5. Development of a machine learning algorithm to predict complications of total laparoscopic anterior resection and natural orifice specimen extraction surgery in rectal cancer.
Wei R; Guan X; Liu E; Zhang W; Lv J; Huang H; Zhao Z; Chen H; Liu Z; Jiang Z; Wang X
Eur J Surg Oncol; 2023 Jul; 49(7):1258-1268. PubMed ID: 36653246
[TBL] [Abstract][Full Text] [Related]
6. A novel method for detection of pancreatic Ductal Adenocarcinoma using explainable machine learning.
Aslam M; Rajbdad F; Azmat S; Li Z; Boudreaux JP; Thiagarajan R; Yao S; Xu J
Comput Methods Programs Biomed; 2024 Mar; 245():108019. PubMed ID: 38237450
[TBL] [Abstract][Full Text] [Related]
7. [Construction of a predictive model for in-hospital mortality of sepsis patients in intensive care unit based on machine learning].
Zhu M; Hu C; He Y; Qian Y; Tang S; Hu Q; Hao C
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul; 35(7):696-701. PubMed ID: 37545445
[TBL] [Abstract][Full Text] [Related]
8. Ten-Year Multicenter Retrospective Study Utilizing Machine Learning Algorithms to Identify Patients at High Risk of Venous Thromboembolism After Radical Gastrectomy.
Liu Y; Song C; Tian Z; Shen W
Int J Gen Med; 2023; 16():1909-1925. PubMed ID: 37228741
[TBL] [Abstract][Full Text] [Related]
9. Development and internal validation of a machine-learning-developed model for predicting 1-year mortality after fragility hip fracture.
Kitcharanant N; Chotiyarnwong P; Tanphiriyakun T; Vanitcharoenkul E; Mahaisavariya C; Boonyaprapa W; Unnanuntana A
BMC Geriatr; 2022 May; 22(1):451. PubMed ID: 35610589
[TBL] [Abstract][Full Text] [Related]
10. Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation.
Lu YT; Chao HJ; Chiang YC; Chen HY
J Med Internet Res; 2023 Feb; 25():e43734. PubMed ID: 36749620
[TBL] [Abstract][Full Text] [Related]
11. Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis.
Mukherjee S; Patra A; Khasawneh H; Korfiatis P; Rajamohan N; Suman G; Majumder S; Panda A; Johnson MP; Larson NB; Wright DE; Kline TL; Fletcher JG; Chari ST; Goenka AH
Gastroenterology; 2022 Nov; 163(5):1435-1446.e3. PubMed ID: 35788343
[TBL] [Abstract][Full Text] [Related]
12. Impact of Intraoperative Data on Risk Prediction for Mortality After Intra-Abdominal Surgery.
Yan X; Goldsmith J; Mohan S; Turnbull ZA; Freundlich RE; Billings FT; Kiran RP; Li G; Kim M
Anesth Analg; 2022 Jan; 134(1):102-113. PubMed ID: 34908548
[TBL] [Abstract][Full Text] [Related]
13. Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma.
Liao H; Yuan J; Liu C; Zhang J; Yang Y; Liang H; Jiang S; Chen S; Li Y; Liu Y
Insights Imaging; 2023 Dec; 14(1):223. PubMed ID: 38129708
[TBL] [Abstract][Full Text] [Related]
14. Comparison of Multiple Radiomics Models for Identifying Histological Grade of Pancreatic Ductal Adenocarcinoma Preoperatively Based on Multiphasic Contrast-Enhanced Computed Tomography: A Two-Center Study in Southwest China.
Liao H; Li Y; Yang Y; Liu H; Zhang J; Liang H; Yan G; Liu Y
Diagnostics (Basel); 2022 Aug; 12(8):. PubMed ID: 36010267
[TBL] [Abstract][Full Text] [Related]
15. Application of machine learning approaches for osteoporosis risk prediction in postmenopausal women.
Shim JG; Kim DW; Ryu KH; Cho EA; Ahn JH; Kim JI; Lee SH
Arch Osteoporos; 2020 Oct; 15(1):169. PubMed ID: 33097976
[TBL] [Abstract][Full Text] [Related]
16. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
[TBL] [Abstract][Full Text] [Related]
17. Machine learning to predict early recurrence after oesophageal cancer surgery.
Rahman SA; Walker RC; Lloyd MA; Grace BL; van Boxel GI; Kingma BF; Ruurda JP; van Hillegersberg R; Harris S; Parsons S; Mercer S; Griffiths EA; O'Neill JR; Turkington R; Fitzgerald RC; Underwood TJ;
Br J Surg; 2020 Jul; 107(8):1042-1052. PubMed ID: 31997313
[TBL] [Abstract][Full Text] [Related]
18. Recurrence prediction of lung adenocarcinoma using an immune gene expression and clinical data trained and validated support vector machine classifier.
Shen Y; Goparaju C; Yang Y; Babu BA; Gai W; Pass H; Jiang G
Transl Lung Cancer Res; 2023 Oct; 12(10):2055-2067. PubMed ID: 38025809
[TBL] [Abstract][Full Text] [Related]
19. A novel online calculator to predict early recurrence and long-term survival of patients with resectable pancreatic ductal adenocarcinoma after pancreaticoduodenectomy: A multicenter study.
Zhang XP; Gao YX; Xu S; Zhao GD; Hu MG; Tan XL; Zhao ZM; Liu R
Int J Surg; 2022 Oct; 106():106891. PubMed ID: 36165934
[TBL] [Abstract][Full Text] [Related]
20. Joint modeling strategy for using electronic medical records data to build machine learning models: an example of intracerebral hemorrhage.
Tang J; Wang X; Wan H; Lin C; Shao Z; Chang Y; Wang H; Wu Y; Zhang T; Du Y
BMC Med Inform Decis Mak; 2022 Oct; 22(1):278. PubMed ID: 36284327
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
