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.


Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

456 related articles for article (PubMed ID: 30458006)

  • 1. Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.
    Rahimian F; Salimi-Khorshidi G; Payberah AH; Tran J; Ayala Solares R; Raimondi F; Nazarzadeh M; Canoy D; Rahimi K
    PLoS Med; 2018 Nov; 15(11):e1002695. PubMed ID: 30458006
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.
    Lin H; Long E; Ding X; Diao H; Chen Z; Liu R; Huang J; Cai J; Xu S; Zhang X; Wang D; Chen K; Yu T; Wu D; Zhao X; Liu Z; Wu X; Jiang Y; Yang X; Cui D; Liu W; Zheng Y; Luo L; Wang H; Chan CC; Morgan IG; He M; Liu Y
    PLoS Med; 2018 Nov; 15(11):e1002674. PubMed ID: 30399150
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.
    Vaid A; Somani S; Russak AJ; De Freitas JK; Chaudhry FF; Paranjpe I; Johnson KW; Lee SJ; Miotto R; Richter F; Zhao S; Beckmann ND; Naik N; Kia A; Timsina P; Lala A; Paranjpe M; Golden E; Danieletto M; Singh M; Meyer D; O'Reilly PF; Huckins L; Kovatch P; Finkelstein J; Freeman RM; Argulian E; Kasarskis A; Percha B; Aberg JA; Bagiella E; Horowitz CR; Murphy B; Nestler EJ; Schadt EE; Cho JH; Cordon-Cardo C; Fuster V; Charney DS; Reich DL; Bottinger EP; Levin MA; Narula J; Fayad ZA; Just AC; Charney AW; Nadkarni GN; Glicksberg BS
    J Med Internet Res; 2020 Nov; 22(11):e24018. PubMed ID: 33027032
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study.
    Corey KM; Kashyap S; Lorenzi E; Lagoo-Deenadayalan SA; Heller K; Whalen K; Balu S; Heflin MT; McDonald SR; Swaminathan M; Sendak M
    PLoS Med; 2018 Nov; 15(11):e1002701. PubMed ID: 30481172
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment.
    Wong A; Young AT; Liang AS; Gonzales R; Douglas VC; Hadley D
    JAMA Netw Open; 2018 Aug; 1(4):e181018. PubMed ID: 30646095
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
    Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK
    Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.
    Huang C; Murugiah K; Mahajan S; Li SX; Dhruva SS; Haimovich JS; Wang Y; Schulz WL; Testani JM; Wilson FP; Mena CI; Masoudi FA; Rumsfeld JS; Spertus JA; Mortazavi BJ; Krumholz HM
    PLoS Med; 2018 Nov; 15(11):e1002703. PubMed ID: 30481186
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.
    Hsu CN; Liu CL; Tain YL; Kuo CY; Lin YC
    J Med Internet Res; 2020 Aug; 22(8):e16903. PubMed ID: 32749223
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting Survival From Large Echocardiography and Electronic Health Record Datasets: Optimization With Machine Learning.
    Samad MD; Ulloa A; Wehner GJ; Jing L; Hartzel D; Good CW; Williams BA; Haggerty CM; Fornwalt BK
    JACC Cardiovasc Imaging; 2019 Apr; 12(4):681-689. PubMed ID: 29909114
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Emergency department triage prediction of clinical outcomes using machine learning models.
    Raita Y; Goto T; Faridi MK; Brown DFM; Camargo CA; Hasegawa K
    Crit Care; 2019 Feb; 23(1):64. PubMed ID: 30795786
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.
    Thorsen-Meyer HC; Nielsen AB; Nielsen AP; Kaas-Hansen BS; Toft P; Schierbeck J; Strøm T; Chmura PJ; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Belling K; Brunak S; Perner A
    Lancet Digit Health; 2020 Apr; 2(4):e179-e191. PubMed ID: 33328078
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.
    Shung DL; Au B; Taylor RA; Tay JK; Laursen SB; Stanley AJ; Dalton HR; Ngu J; Schultz M; Laine L
    Gastroenterology; 2020 Jan; 158(1):160-167. PubMed ID: 31562847
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.
    Herrin J; Abraham NS; Yao X; Noseworthy PA; Inselman J; Shah ND; Ngufor C
    JAMA Netw Open; 2021 May; 4(5):e2110703. PubMed ID: 34019087
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting risk of emergency admission to hospital using primary care data: derivation and validation of QAdmissions score.
    Hippisley-Cox J; Coupland C
    BMJ Open; 2013 Aug; 3(8):e003482. PubMed ID: 23959760
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data.
    Rojas JC; Carey KA; Edelson DP; Venable LR; Howell MD; Churpek MM
    Ann Am Thorac Soc; 2018 Jul; 15(7):846-853. PubMed ID: 29787309
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Machine-learning Models Predict 30-Day Mortality, Cardiovascular Complications, and Respiratory Complications After Aseptic Revision Total Joint Arthroplasty.
    Abraham VM; Booth G; Geiger P; Balazs GC; Goldman A
    Clin Orthop Relat Res; 2022 Nov; 480(11):2137-2145. PubMed ID: 35767804
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting hospital admission for older emergency department patients: Insights from machine learning.
    Mowbray F; Zargoush M; Jones A; de Wit K; Costa A
    Int J Med Inform; 2020 Aug; 140():104163. PubMed ID: 32474393
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Risk prediction models to predict emergency hospital admission in community-dwelling adults: a systematic review.
    Wallace E; Stuart E; Vaughan N; Bennett K; Fahey T; Smith SM
    Med Care; 2014 Aug; 52(8):751-65. PubMed ID: 25023919
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.