BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

500 related articles for article (PubMed ID: 35004312)

  • 1. Trends in Development of Novel Machine Learning Methods for the Identification of Gliomas in Datasets That Include Non-Glioma Images: A Systematic Review.
    Subramanian H; Dey R; Brim WR; Tillmanns N; Cassinelli Petersen G; Brackett A; Mahajan A; Johnson M; Malhotra A; Aboian M
    Front Oncol; 2021; 11():788819. PubMed ID: 35004312
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis.
    Bahar RC; Merkaj S; Cassinelli Petersen GI; Tillmanns N; Subramanian H; Brim WR; Zeevi T; Staib L; Kazarian E; Lin M; Bousabarah K; Huttner AJ; Pala A; Payabvash S; Ivanidze J; Cui J; Malhotra A; Aboian MS
    Front Oncol; 2022; 12():856231. PubMed ID: 35530302
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Beyond the black stump: rapid reviews of health research issues affecting regional, rural and remote Australia.
    Osborne SR; Alston LV; Bolton KA; Whelan J; Reeve E; Wong Shee A; Browne J; Walker T; Versace VL; Allender S; Nichols M; Backholer K; Goodwin N; Lewis S; Dalton H; Prael G; Curtin M; Brooks R; Verdon S; Crockett J; Hodgins G; Walsh S; Lyle DM; Thompson SC; Browne LJ; Knight S; Pit SW; Jones M; Gillam MH; Leach MJ; Gonzalez-Chica DA; Muyambi K; Eshetie T; Tran K; May E; Lieschke G; Parker V; Smith A; Hayes C; Dunlop AJ; Rajappa H; White R; Oakley P; Holliday S
    Med J Aust; 2020 Dec; 213 Suppl 11():S3-S32.e1. PubMed ID: 33314144
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment.
    Cassinelli Petersen GI; Shatalov J; Verma T; Brim WR; Subramanian H; Brackett A; Bahar RC; Merkaj S; Zeevi T; Staib LH; Cui J; Omuro A; Bronen RA; Malhotra A; Aboian MS
    AJNR Am J Neuroradiol; 2022 Apr; 43(4):526-533. PubMed ID: 35361577
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The future of Cochrane Neonatal.
    Soll RF; Ovelman C; McGuire W
    Early Hum Dev; 2020 Nov; 150():105191. PubMed ID: 33036834
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.
    Nagendran M; Chen Y; Lovejoy CA; Gordon AC; Komorowski M; Harvey H; Topol EJ; Ioannidis JPA; Collins GS; Maruthappu M
    BMJ; 2020 Mar; 368():m689. PubMed ID: 32213531
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries.
    Tillmanns N; Lum AE; Cassinelli G; Merkaj S; Verma T; Zeevi T; Staib L; Subramanian H; Bahar RC; Brim W; Lost J; Jekel L; Brackett A; Payabvash S; Ikuta I; Lin M; Bousabarah K; Johnson MH; Cui J; Malhotra A; Omuro A; Turowski B; Aboian MS
    Neurooncol Adv; 2022; 4(1):vdac093. PubMed ID: 36071926
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction.
    Lost J; Verma T; Jekel L; von Reppert M; Tillmanns N; Merkaj S; Petersen GC; Bahar R; Gordem A; Haider MA; Subramanian H; Brim W; Ikuta I; Omuro A; Conte GM; Marquez-Nostra BV; Avesta A; Bousabarah K; Nabavizadeh A; Kazerooni AF; Aneja S; Bakas S; Lin M; Sabel M; Aboian M
    AJNR Am J Neuroradiol; 2023 Oct; 44(10):1126-1134. PubMed ID: 37770204
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Current state of radiomics in pediatric neuro-oncology practice: a systematic review.
    Albalkhi I; Bhatia A; Lösch N; Goetti R; Mankad K
    Pediatr Radiol; 2023 Sep; 53(10):2079-2091. PubMed ID: 37195305
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Systematic review and modelling of the cost-effectiveness of cardiac magnetic resonance imaging compared with current existing testing pathways in ischaemic cardiomyopathy.
    Campbell F; Thokala P; Uttley LC; Sutton A; Sutton AJ; Al-Mohammad A; Thomas SM
    Health Technol Assess; 2014 Sep; 18(59):1-120. PubMed ID: 25265259
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine Learning Applications for Differentiation of Glioma from Brain Metastasis-A Systematic Review.
    Jekel L; Brim WR; von Reppert M; Staib L; Cassinelli Petersen G; Merkaj S; Subramanian H; Zeevi T; Payabvash S; Bousabarah K; Lin M; Cui J; Brackett A; Mahajan A; Omuro A; Johnson MH; Chiang VL; Malhotra A; Scheffler B; Aboian MS
    Cancers (Basel); 2022 Mar; 14(6):. PubMed ID: 35326526
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review.
    Buchlak QD; Esmaili N; Leveque JC; Bennett C; Farrokhi F; Piccardi M
    J Clin Neurosci; 2021 Jul; 89():177-198. PubMed ID: 34119265
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis.
    Jian A; Jang K; Manuguerra M; Liu S; Magnussen J; Di Ieva A
    Neurosurgery; 2021 Jun; 89(1):31-44. PubMed ID: 33826716
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Diagnostic Accuracy of Artificial Intelligence Based on Imaging Data for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.
    Zhang J; Huang S; Xu Y; Wu J
    Front Oncol; 2022; 12():763842. PubMed ID: 35280776
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis.
    van Kempen EJ; Post M; Mannil M; Witkam RL; Ter Laan M; Patel A; Meijer FJA; Henssen D
    Eur Radiol; 2021 Dec; 31(12):9638-9653. PubMed ID: 34019128
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review.
    Hansun S; Argha A; Liaw ST; Celler BG; Marks GB
    J Med Internet Res; 2023 Jul; 25():e43154. PubMed ID: 37399055
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review.
    Ferreira-Santos D; Amorim P; Silva Martins T; Monteiro-Soares M; Pereira Rodrigues P
    J Med Internet Res; 2022 Sep; 24(9):e39452. PubMed ID: 36178720
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Randomized Clinical Trials of Machine Learning Interventions in Health Care: A Systematic Review.
    Plana D; Shung DL; Grimshaw AA; Saraf A; Sung JJY; Kann BH
    JAMA Netw Open; 2022 Sep; 5(9):e2233946. PubMed ID: 36173632
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Digital Education for the Management of Chronic Wounds in Health Care Professionals: Protocol for a Systematic Review by the Digital Health Education Collaboration.
    Martinengo L; Yeo NJY; Tang ZQ; Markandran KD; Kyaw BM; Tudor Car L
    JMIR Res Protoc; 2019 Mar; 8(3):e12488. PubMed ID: 30907743
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Reporting of Model Performance and Statistical Methods in Studies That Use Machine Learning to Develop Clinical Prediction Models: Protocol for a Systematic Review.
    Weaver CGW; Basmadjian RB; Williamson T; McBrien K; Sajobi T; Boyne D; Yusuf M; Ronksley PE
    JMIR Res Protoc; 2022 Mar; 11(3):e30956. PubMed ID: 35238322
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 25.