BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

165 related articles for article (PubMed ID: 34525441)

  • 1. Predicting length of stay and mortality among hospitalized patients with type 2 diabetes mellitus and hypertension.
    Barsasella D; Gupta S; Malwade S; Aminin ; Susanti Y; Tirmadi B; Mutamakin A; Jonnagaddala J; Syed-Abdul S
    Int J Med Inform; 2021 Oct; 154():104569. PubMed ID: 34525441
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Machine Learning Model to Predict Length of Stay and Mortality among Diabetes and Hypertension Inpatients.
    Barsasella D; Bah K; Mishra P; Uddin M; Dhar E; Suryani DL; Setiadi D; Masturoh I; Sugiarti I; Jonnagaddala J; Syed-Abdul S
    Medicina (Kaunas); 2022 Oct; 58(11):. PubMed ID: 36363525
    [No Abstract]   [Full Text] [Related]  

  • 3. Prediction of mortality risk and duration of hospitalization of COVID-19 patients with chronic comorbidities based on machine learning algorithms.
    Amiri P; Montazeri M; Ghasemian F; Asadi F; Niksaz S; Sarafzadeh F; Khajouei R
    Digit Health; 2023; 9():20552076231170493. PubMed ID: 37312960
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predictors of in-hospital length of stay among cardiac patients: A machine learning approach.
    Daghistani TA; Elshawi R; Sakr S; Ahmed AM; Al-Thwayee A; Al-Mallah MH
    Int J Cardiol; 2019 Aug; 288():140-147. PubMed ID: 30685103
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis.
    Zeleke AJ; Palumbo P; Tubertini P; Miglio R; Chiari L
    Front Artif Intell; 2023; 6():1179226. PubMed ID: 37588696
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty.
    Abbas A; Mosseri J; Lex JR; Toor J; Ravi B; Khalil EB; Whyne C
    Int J Med Inform; 2022 Feb; 158():104670. PubMed ID: 34971918
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Performance of Artificial Intelligence-Based Algorithms to Predict Prolonged Length of Stay after Lumbar Decompression Surgery.
    Saravi B; Zink A; Ülkümen S; Couillard-Despres S; Hassel F; Lang G
    J Clin Med; 2022 Jul; 11(14):. PubMed ID: 35887814
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparing artificial neural network training algorithms to predict length of stay in hospitalized patients with COVID-19.
    Orooji A; Shanbehzadeh M; Mirbagheri E; Kazemi-Arpanahi H
    BMC Infect Dis; 2022 Dec; 22(1):923. PubMed ID: 36494613
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach.
    Gopukumar D; Ghoshal A; Zhao H
    JMIR Med Inform; 2022 Aug; 10(8):e37578. PubMed ID: 35896038
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting Inpatient Length of Stay After Brain Tumor Surgery: Developing Machine Learning Ensembles to Improve Predictive Performance.
    Muhlestein WE; Akagi DS; Davies JM; Chambless LB
    Neurosurgery; 2019 Sep; 85(3):384-393. PubMed ID: 30113665
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Does state malpractice environment affect outcomes following spinal fusions? A robust statistical and machine learning analysis of 549,775 discharges following spinal fusion surgery in the United States.
    Chan AK; Santacatterina M; Pennicooke B; Shahrestani S; Ballatori AM; Orrico KO; Burke JF; Manley GT; Tarapore PE; Huang MC; Dhall SS; Chou D; Mummaneni PV; DiGiorgio AM
    Neurosurg Focus; 2020 Nov; 49(5):E18. PubMed ID: 33130616
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Consultation length and no-show prediction for improving appointment scheduling efficiency at a cardiology clinic: A data analytics approach.
    Srinivas S; Salah H
    Int J Med Inform; 2021 Jan; 145():104290. PubMed ID: 33099184
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.
    Huang JC; Tsai YC; Wu PY; Lien YH; Chien CY; Kuo CF; Hung JF; Chen SC; Kuo CH
    Comput Methods Programs Biomed; 2020 Oct; 195():105536. PubMed ID: 32485511
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests.
    Xu S; Hom J; Balasubramanian S; Schroeder LF; Najafi N; Roy S; Chen JH
    JAMA Netw Open; 2019 Sep; 2(9):e1910967. PubMed ID: 31509205
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Hospital Length of Stay and 30-Day Mortality Prediction in Stroke: A Machine Learning Analysis of 17,000 ICU Admissions in Brazil.
    Kurtz P; Peres IT; Soares M; Salluh JIF; Bozza FA
    Neurocrit Care; 2022 Aug; 37(Suppl 2):313-321. PubMed ID: 35381967
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning models to predict length of stay and discharge destination in complex head and neck surgery.
    Goshtasbi K; Yasaka TM; Zandi-Toghani M; Djalilian HR; Armstrong WB; Tjoa T; Haidar YM; Abouzari M
    Head Neck; 2021 Mar; 43(3):788-797. PubMed ID: 33142001
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Beyond the Bedside: Machine Learning-Guided Length of Stay (LOS) Prediction for Cardiac Patients in Tertiary Care.
    AlMuhaideb S; Bin Shawyah A; Alhamid MF; Alabbad A; Alabbad M; Alsergani H; Alswailem O
    Healthcare (Basel); 2024 May; 12(11):. PubMed ID: 38891185
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Investigating Predictors of Increased Length of Stay After Resection of Vestibular Schwannoma Using Machine Learning.
    Dang S; Manzoor NF; Chowdhury N; Tittman SM; Yancey KL; Monsour MA; O'Malley MR; Rivas A; Haynes DS; Bennett ML
    Otol Neurotol; 2021 Jun; 42(5):e584-e592. PubMed ID: 33443974
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Assessment of hospital length of stay and direct costs of type 2 diabetes in Hubei Province, China.
    Chen D; Liu S; Tan X; Zhao Q
    BMC Health Serv Res; 2017 Mar; 17(1):199. PubMed ID: 28288623
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Parsimonious machine learning models to predict resource use in cardiac surgery across a statewide collaborative.
    Verma A; Sanaiha Y; Hadaya J; Maltagliati AJ; Tran Z; Ramezani R; Shemin RJ; Benharash P;
    JTCVS Open; 2022 Sep; 11():214-228. PubMed ID: 36172420
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.