BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

239 related articles for article (PubMed ID: 31845194)

  • 21. Prediction of different types of liver diseases using rule based classification model.
    Kumar Y; Sahoo G
    Technol Health Care; 2013; 21(5):417-32. PubMed ID: 23963359
    [TBL] [Abstract][Full Text] [Related]  

  • 22. R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification.
    Bania RK; Halder A
    Artif Intell Med; 2021 Apr; 114():102049. PubMed ID: 33875164
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.
    Pérez NP; Guevara López MA; Silva A; Ramos I
    Artif Intell Med; 2015 Jan; 63(1):19-31. PubMed ID: 25555756
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies.
    Hussain L; Saeed S; Awan IA; Idris A; Nadeem MSA; Chaudhry QU
    Curr Med Imaging Rev; 2019; 15(6):595-606. PubMed ID: 32008569
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Fetal health status prediction based on maternal clinical history using machine learning techniques.
    Akbulut A; Ertugrul E; Topcu V
    Comput Methods Programs Biomed; 2018 Sep; 163():87-100. PubMed ID: 30119860
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network.
    Elgin Christo VR; Khanna Nehemiah H; Minu B; Kannan A
    Comput Math Methods Med; 2019; 2019():7398307. PubMed ID: 31662787
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Precision healthcare: A deep dive into machine learning algorithms and feature selection strategies for accurate heart disease prediction.
    Islam MA; Majumder MZH; Miah MS; Jannaty S
    Comput Biol Med; 2024 Jun; 176():108432. PubMed ID: 38744014
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Developing Multiagent E-Learning System-Based Machine Learning and Feature Selection Techniques.
    Hessen SH; Abdul-Kader HM; Khedr AE; Salem RK
    Comput Intell Neurosci; 2022; 2022():2941840. PubMed ID: 35140765
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Analyzing the impact of feature selection methods on machine learning algorithms for heart disease prediction.
    Noroozi Z; Orooji A; Erfannia L
    Sci Rep; 2023 Dec; 13(1):22588. PubMed ID: 38114600
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A novel cumulative level difference mean based GLDM and modified ABCD features ranked using eigenvector centrality approach for four skin lesion types classification.
    Wahba MA; Ashour AS; Guo Y; Napoleon SA; Elnaby MMA
    Comput Methods Programs Biomed; 2018 Oct; 165():163-174. PubMed ID: 30337071
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Comparing different supervised machine learning algorithms for disease prediction.
    Uddin S; Khan A; Hossain ME; Moni MA
    BMC Med Inform Decis Mak; 2019 Dec; 19(1):281. PubMed ID: 31864346
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.
    Bektas CT; Kocak B; Yardimci AH; Turkcanoglu MH; Yucetas U; Koca SB; Erdim C; Kilickesmez O
    Eur Radiol; 2019 Mar; 29(3):1153-1163. PubMed ID: 30167812
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Heterogeneous Ensemble Deep Learning Model for Enhanced Arabic Sentiment Analysis.
    Saleh H; Mostafa S; Alharbi A; El-Sappagh S; Alkhalifah T
    Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632116
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Classification of Skin Disease using Ensemble Data Mining Techniques.
    Verma AK; Pal S; Kumar S
    Asian Pac J Cancer Prev; 2019 Jun; 20(6):1887-1894. PubMed ID: 31244314
    [TBL] [Abstract][Full Text] [Related]  

  • 35. 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]  

  • 36. A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection.
    Liu Y; Guo Y; Wu W; Xiong Y; Sun C; Yuan L; Li M
    Interdiscip Sci; 2019 Dec; 11(4):738-747. PubMed ID: 31486019
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques.
    Sahu R; Dash SR; Cacha LA; Poznanski RR; Parida S
    J Integr Neurosci; 2020 Mar; 19(1):1-9. PubMed ID: 32259881
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.
    Hussain L; Ahmed A; Saeed S; Rathore S; Awan IA; Shah SA; Majid A; Idris A; Awan AA
    Cancer Biomark; 2018 Feb; 21(2):393-413. PubMed ID: 29226857
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Early detection of Parkinson disease using stacking ensemble method.
    Biswas SK; Nath Boruah A; Saha R; Raj RS; Chakraborty M; Bordoloi M
    Comput Methods Biomech Biomed Engin; 2023 Apr; 26(5):527-539. PubMed ID: 35587795
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Predicting sustainable arsenic mitigation using machine learning techniques.
    Singh SK; Taylor RW; Pradhan B; Shirzadi A; Pham BT
    Ecotoxicol Environ Saf; 2022 Mar; 232():113271. PubMed ID: 35121252
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 12.