These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
197 related articles for article (PubMed ID: 36305042)
1. Development and international validation of logistic regression and machine-learning models for the prediction of 10-year molar loss. Troiano G; Nibali L; Petsos H; Eickholz P; Saleh MHA; Santamaria P; Jian J; Shi S; Meng H; Zhurakivska K; Wang HL; Ravidà A J Clin Periodontol; 2023 Mar; 50(3):348-357. PubMed ID: 36305042 [TBL] [Abstract][Full Text] [Related]
2. Establishment and validation of an interactive artificial intelligence platform to predict postoperative ambulatory status for patients with metastatic spinal disease: a multicenter analysis. Cui Y; Shi X; Qin Y; Wang Q; Cao X; Che X; Pan Y; Wang B; Lei M; Liu Y Int J Surg; 2024 May; 110(5):2738-2756. PubMed ID: 38376838 [TBL] [Abstract][Full Text] [Related]
3. Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers. Deist TM; Dankers FJWM; Valdes G; Wijsman R; Hsu IC; Oberije C; Lustberg T; van Soest J; Hoebers F; Jochems A; El Naqa I; Wee L; Morin O; Raleigh DR; Bots W; Kaanders JH; Belderbos J; Kwint M; Solberg T; Monshouwer R; Bussink J; Dekker A; Lambin P Med Phys; 2018 Jul; 45(7):3449-3459. PubMed ID: 29763967 [TBL] [Abstract][Full Text] [Related]
4. A systematic comparison of machine learning algorithms to develop and validate prediction model to predict heart failure risk in middle-aged and elderly patients with periodontitis (NHANES 2009 to 2014). Wang Y; Xiao Y; Zhang Y Medicine (Baltimore); 2023 Aug; 102(34):e34878. PubMed ID: 37653785 [TBL] [Abstract][Full Text] [Related]
5. Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms. Nhu VH; Shirzadi A; Shahabi H; Singh SK; Al-Ansari N; Clague JJ; Jaafari A; Chen W; Miraki S; Dou J; Luu C; Górski K; Thai Pham B; Nguyen HD; Ahmad BB Int J Environ Res Public Health; 2020 Apr; 17(8):. PubMed ID: 32316191 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers. Kawakami E; Tabata J; Yanaihara N; Ishikawa T; Koseki K; Iida Y; Saito M; Komazaki H; Shapiro JS; Goto C; Akiyama Y; Saito R; Saito M; Takano H; Yamada K; Okamoto A Clin Cancer Res; 2019 May; 25(10):3006-3015. PubMed ID: 30979733 [TBL] [Abstract][Full Text] [Related]
8. Can Machine-learning Techniques Be Used for 5-year Survival Prediction of Patients With Chondrosarcoma? Thio QCBS; Karhade AV; Ogink PT; Raskin KA; De Amorim Bernstein K; Lozano Calderon SA; Schwab JH Clin Orthop Relat Res; 2018 Oct; 476(10):2040-2048. PubMed ID: 30179954 [TBL] [Abstract][Full Text] [Related]
9. Machine Learning Approaches to Predict Chronic Lower Back Pain in People Aged over 50 Years. Shim JG; Ryu KH; Cho EA; Ahn JH; Kim HK; Lee YJ; Lee SH Medicina (Kaunas); 2021 Nov; 57(11):. PubMed ID: 34833448 [No Abstract] [Full Text] [Related]
10. 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]
11. Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status. Kocak B; Durmaz ES; Ates E; Sel I; Turgut Gunes S; Kaya OK; Zeynalova A; Kilickesmez O Eur Radiol; 2020 Feb; 30(2):877-886. PubMed ID: 31691122 [TBL] [Abstract][Full Text] [Related]
12. Development and Internal Validation of Machine Learning Algorithms for Preoperative Survival Prediction of Extremity Metastatic Disease. Thio QCBS; Karhade AV; Bindels BJJ; Ogink PT; Bramer JAM; Ferrone ML; Calderón SL; Raskin KA; Schwab JH Clin Orthop Relat Res; 2020 Feb; 478(2):322-333. PubMed ID: 31651589 [TBL] [Abstract][Full Text] [Related]
13. Classification of imbalanced data using machine learning algorithms to predict the risk of renal graft failures in Ethiopia. Mulugeta G; Zewotir T; Tegegne AS; Juhar LH; Muleta MB BMC Med Inform Decis Mak; 2023 May; 23(1):98. PubMed ID: 37217892 [TBL] [Abstract][Full Text] [Related]
14. A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm. Zhou CM; Xue Q; Li H; Yang JJ; Zhu Y Sci Rep; 2024 Mar; 14(1):7035. PubMed ID: 38528066 [TBL] [Abstract][Full Text] [Related]
15. Comparison of Support Vector Machine, Naïve Bayes and Logistic Regression for Assessing the Necessity for Coronary Angiography. Golpour P; Ghayour-Mobarhan M; Saki A; Esmaily H; Taghipour A; Tajfard M; Ghazizadeh H; Moohebati M; Ferns GA Int J Environ Res Public Health; 2020 Sep; 17(18):. PubMed ID: 32899733 [TBL] [Abstract][Full Text] [Related]
16. Chronic stress in practice assistants: An analytic approach comparing four machine learning classifiers with a standard logistic regression model. Bozorgmehr A; Thielmann A; Weltermann B PLoS One; 2021; 16(5):e0250842. PubMed ID: 33945572 [TBL] [Abstract][Full Text] [Related]
17. Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study. Aguirre U; Urrechaga E Clin Chem Lab Med; 2023 Jan; 61(2):356-365. PubMed ID: 36351434 [TBL] [Abstract][Full Text] [Related]
18. Machine learning versus logistic regression for prognostic modelling in individuals with non-specific neck pain. Liew BXW; Kovacs FM; Rügamer D; Royuela A Eur Spine J; 2022 Aug; 31(8):2082-2091. PubMed ID: 35353221 [TBL] [Abstract][Full Text] [Related]
19. Prediction of postoperative complications after oesophagectomy using machine-learning methods. Jung JO; Pisula JI; Bozek K; Popp F; Fuchs HF; Schröder W; Bruns CJ; Schmidt T Br J Surg; 2023 Sep; 110(10):1361-1366. PubMed ID: 37343072 [TBL] [Abstract][Full Text] [Related]
20. Machine Learning-Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study. Luo XQ; Kang YX; Duan SB; Yan P; Song GB; Zhang NY; Yang SK; Li JX; Zhang H J Med Internet Res; 2023 Jan; 25():e41142. PubMed ID: 36603200 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]