BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

143 related articles for article (PubMed ID: 28553366)

  • 1. Dysphonic Voice Pattern Analysis of Patients in Parkinson's Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods.
    Wu Y; Chen P; Yao Y; Ye X; Xiao Y; Liao L; Wu M; Chen J
    Comput Math Methods Med; 2017; 2017():4201984. PubMed ID: 28553366
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Effective dysphonia detection using feature dimension reduction and kernel density estimation for patients with Parkinson's disease.
    Yang S; Zheng F; Luo X; Cai S; Wu Y; Liu K; Wu M; Chen J; Krishnan S
    PLoS One; 2014; 9(2):e88825. PubMed ID: 24586406
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Classification of Dysphonic Voices in Parkinson's Disease with Semi-Supervised Competitive Learning Algorithm.
    Bao G; Lin M; Sang X; Hou Y; Liu Y; Wu Y
    Biosensors (Basel); 2022 Jul; 12(7):. PubMed ID: 35884305
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Data-driven diagnosis of spinal abnormalities using feature selection and machine learning algorithms.
    Raihan-Al-Masud M; Mondal MRH
    PLoS One; 2020; 15(2):e0228422. PubMed ID: 32027680
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A new hybrid intelligent system for accurate detection of Parkinson's disease.
    Hariharan M; Polat K; Sindhu R
    Comput Methods Programs Biomed; 2014 Mar; 113(3):904-13. PubMed ID: 24485390
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SVM feature selection based rotation forest ensemble classifiers to improve computer-aided diagnosis of Parkinson disease.
    Ozcift A
    J Med Syst; 2012 Aug; 36(4):2141-7. PubMed ID: 21547504
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Performance of machine learning methods in diagnosing Parkinson's disease based on dysphonia measures.
    Lahmiri S; Dawson DA; Shmuel A
    Biomed Eng Lett; 2018 Feb; 8(1):29-39. PubMed ID: 30603188
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.
    S K S; P A
    J Med Syst; 2017 Nov; 41(12):201. PubMed ID: 29124453
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning in automatic detection of dysphonia: Comparing acoustic features and developing a generalizable framework.
    Chen Z; Zhu P; Qiu W; Guo J; Li Y
    Int J Lang Commun Disord; 2023 Mar; 58(2):279-294. PubMed ID: 36117378
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluation of train and test performance of machine learning algorithms and Parkinson diagnosis with statistical measurements.
    Avuçlu E; Elen A
    Med Biol Eng Comput; 2020 Nov; 58(11):2775-2788. PubMed ID: 32920727
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Use of machine learning method on automatic classification of motor subtype of Parkinson's disease based on multilevel indices of rs-fMRI.
    Pang H; Yu Z; Yu H; Cao J; Li Y; Guo M; Cao C; Fan G
    Parkinsonism Relat Disord; 2021 Sep; 90():65-72. PubMed ID: 34399160
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Inter classifier comparison to detect voice pathologies.
    Syed SA; Rashid M; Hussain S; Imtiaz A; Abid H; Zahid H
    Math Biosci Eng; 2021 Mar; 18(3):2258-2273. PubMed ID: 33892544
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The accuracy of an Online Sequential Extreme Learning Machine in detecting voice pathology using the Malaysian Voice Pathology Database.
    Za'im NAN; Al-Dhief FT; Azman M; Alsemawi MRM; Abdul Latiff NMA; Mat Baki M
    J Otolaryngol Head Neck Surg; 2023 Sep; 52(1):62. PubMed ID: 37730624
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Early diagnosis of Parkinson's disease using machine learning algorithms.
    Karapinar Senturk Z
    Med Hypotheses; 2020 May; 138():109603. PubMed ID: 32028195
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Diagnosis and classification of Parkinson's disease using ensemble learning and 1D-PDCovNN.
    Nour M; Senturk U; Polat K
    Comput Biol Med; 2023 Jul; 161():107031. PubMed ID: 37211002
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Statistical analysis of the reliability of acoustic and electroglottographic perturbation parameters for the detection of vocal roughness.
    Hosokawa K; Ogawa M; Hashimoto M; Inohara H
    J Voice; 2014 Mar; 28(2):263.e9-263.e16. PubMed ID: 24216270
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Solving the class imbalance problem using ensemble algorithm: application of screening for aortic dissection.
    Liu L; Wu X; Li S; Li Y; Tan S; Bai Y
    BMC Med Inform Decis Mak; 2022 Mar; 22(1):82. PubMed ID: 35346181
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification.
    Lee HS; Hong H; Jung DC; Park S; Kim J
    Med Phys; 2017 Jul; 44(7):3604-3614. PubMed ID: 28376281
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Selection of vocal features for Parkinson's Disease diagnosis.
    Kursun O; Gumus E; Sertbas A; Favorov OV
    Int J Data Min Bioinform; 2012; 6(2):144-61. PubMed ID: 22724295
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Analysis of altered gait cycle duration in amyotrophic lateral sclerosis based on nonparametric probability density function estimation.
    Wu Y; Shi L
    Med Eng Phys; 2011 Apr; 33(3):347-55. PubMed ID: 21130016
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.