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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

605 related articles for article (PubMed ID: 31842878)

  • 21. External Validation of a Machine Learning Algorithm for Predicting Clinically Meaningful Functional Improvement After Arthroscopic Hip Preservation Surgery.
    Kunze KN; Kaidi A; Madjarova S; Polce EM; Ranawat AS; Nawabi DH; Kelly BT; Nho SJ; Nwachukwu BU
    Am J Sports Med; 2022 Nov; 50(13):3593-3599. PubMed ID: 36135373
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Development of machine learning algorithms for prediction of discharge disposition after elective inpatient surgery for lumbar degenerative disc disorders.
    Karhade AV; Ogink P; Thio Q; Broekman M; Cha T; Gormley WB; Hershman S; Peul WC; Bono CM; Schwab JH
    Neurosurg Focus; 2018 Nov; 45(5):E6. PubMed ID: 30453463
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis.
    Allotey J; Snell KI; Smuk M; Hooper R; Chan CL; Ahmed A; Chappell LC; von Dadelszen P; Dodds J; Green M; Kenny L; Khalil A; Khan KS; Mol BW; Myers J; Poston L; Thilaganathan B; Staff AC; Smith GC; Ganzevoort W; Laivuori H; Odibo AO; Ramírez JA; Kingdom J; Daskalakis G; Farrar D; Baschat AA; Seed PT; Prefumo F; da Silva Costa F; Groen H; Audibert F; Masse J; Skråstad RB; Salvesen KÅ; Haavaldsen C; Nagata C; Rumbold AR; Heinonen S; Askie LM; Smits LJ; Vinter CA; Magnus PM; Eero K; Villa PM; Jenum AK; Andersen LB; Norman JE; Ohkuchi A; Eskild A; Bhattacharya S; McAuliffe FM; Galindo A; Herraiz I; Carbillon L; Klipstein-Grobusch K; Yeo S; Teede HJ; Browne JL; Moons KG; Riley RD; Thangaratinam S
    Health Technol Assess; 2020 Dec; 24(72):1-252. PubMed ID: 33336645
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Detection of calibration drift in clinical prediction models to inform model updating.
    Davis SE; Greevy RA; Lasko TA; Walsh CG; Matheny ME
    J Biomed Inform; 2020 Dec; 112():103611. PubMed ID: 33157313
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Illness severity assessment of older adults in critical illness using machine learning (ELDER-ICU): an international multicentre study with subgroup bias evaluation.
    Liu X; Hu P; Yeung W; Zhang Z; Ho V; Liu C; Dumontier C; Thoral PJ; Mao Z; Cao D; Mark RG; Zhang Z; Feng M; Li D; Celi LA
    Lancet Digit Health; 2023 Oct; 5(10):e657-e667. PubMed ID: 37599147
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.
    Pan P; Li Y; Xiao Y; Han B; Su L; Su M; Li Y; Zhang S; Jiang D; Chen X; Zhou F; Ma L; Bao P; Xie L
    J Med Internet Res; 2020 Nov; 22(11):e23128. PubMed ID: 33035175
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.
    Kunze KN; Polce EM; Clapp I; Nwachukwu BU; Chahla J; Nho SJ
    J Bone Joint Surg Am; 2021 Jun; 103(12):1055-1062. PubMed ID: 33877058
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Beyond discrimination: A comparison of calibration methods and clinical usefulness of predictive models of readmission risk.
    Walsh CG; Sharman K; Hripcsak G
    J Biomed Inform; 2017 Dec; 76():9-18. PubMed ID: 29079501
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Does the SORG Orthopaedic Research Group Hip Fracture Delirium Algorithm Perform Well on an Independent Intercontinental Cohort of Patients With Hip Fractures Who Are 60 Years or Older?
    Oosterhoff JHF; Oberai T; Karhade AV; Doornberg JN; Kerkhoffs GMMJ; Jaarsma RL; Schwab JH; Heng M
    Clin Orthop Relat Res; 2022 Nov; 480(11):2205-2213. PubMed ID: 35561268
    [TBL] [Abstract][Full Text] [Related]  

  • 30. 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]  

  • 31. Patients With Femoral Neck Fractures Are at Risk for Conversion to Arthroplasty After Internal Fixation: A Machine-learning Algorithm.
    van de Kuit A; Oosterhoff JHF; Dijkstra H; Sprague S; Bzovsky S; Bhandari M; Swiontkowski M; Schemitsch EH; IJpma FFA; Poolman RW; Doornberg JN; Hendrickx LAM;
    Clin Orthop Relat Res; 2022 Dec; 480(12):2350-2360. PubMed ID: 35767811
    [TBL] [Abstract][Full Text] [Related]  

  • 32. IOT-Based Medical Informatics Farming System with Predictive Data Analytics Using Supervised Machine Learning Algorithms.
    Rokade A; Singh M; Arora SK; Nizeyimana E
    Comput Math Methods Med; 2022; 2022():8434966. PubMed ID: 36081435
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Personal Health Information Inference Using Machine Learning on RNA Expression Data from Patients With Cancer: Algorithm Validation Study.
    Kweon S; Lee JH; Lee Y; Park YR
    J Med Internet Res; 2020 Aug; 22(8):e18387. PubMed ID: 32773372
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables.
    Talaei-Khoei A; Wilson JM
    Int J Med Inform; 2018 Nov; 119():22-38. PubMed ID: 30342683
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Using machine learning to identify patients at high risk of developing low bone density or osteoporosis after gastrectomy: a 10-year multicenter retrospective analysis.
    Zhu Y; Liu Y; Wang Q; Niu S; Wang L; Cheng C; Chen X; Liu J; Zhao S
    J Cancer Res Clin Oncol; 2023 Dec; 149(19):17479-17493. PubMed ID: 37897658
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?
    Fontana MA; Lyman S; Sarker GK; Padgett DE; MacLean CH
    Clin Orthop Relat Res; 2019 Jun; 477(6):1267-1279. PubMed ID: 31094833
    [TBL] [Abstract][Full Text] [Related]  

  • 37. There is no such thing as a validated prediction model.
    Van Calster B; Steyerberg EW; Wynants L; van Smeden M
    BMC Med; 2023 Feb; 21(1):70. PubMed ID: 36829188
    [TBL] [Abstract][Full Text] [Related]  

  • 38. How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data.
    Li Q; Yao X; Échevin D
    Value Health; 2020 Oct; 23(10):1307-1315. PubMed ID: 33032774
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation.
    Hae H; Kang SJ; Kim WJ; Choi SY; Lee JG; Bae Y; Cho H; Yang DH; Kang JW; Lim TH; Lee CH; Kang DY; Lee PH; Ahn JM; Park DW; Lee SW; Kim YH; Lee CW; Park SW; Park SJ
    PLoS Med; 2018 Nov; 15(11):e1002693. PubMed ID: 30422987
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Predicting 90-Day and 1-Year Mortality in Spinal Metastatic Disease: Development and Internal Validation.
    Karhade AV; Thio QCBS; Ogink PT; Bono CM; Ferrone ML; Oh KS; Saylor PJ; Schoenfeld AJ; Shin JH; Harris MB; Schwab JH
    Neurosurgery; 2019 Oct; 85(4):E671-E681. PubMed ID: 30869143
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 31.