BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

228 related articles for article (PubMed ID: 36187616)

  • 21. Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure.
    Qiu H; Luo L; Su Z; Zhou L; Wang L; Chen Y
    BMC Med Inform Decis Mak; 2020 May; 20(1):83. PubMed ID: 32357880
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy.
    Xu Y; Sun X; Liu Y; Huang Y; Liang M; Sun R; Yin G; Song C; Ding Q; Du B; Bi X
    Front Neurol; 2023; 14():1123607. PubMed ID: 37416313
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A comparative analysis of eight machine learning models for the prediction of lateral lymph node metastasis in patients with papillary thyroid carcinoma.
    Feng JW; Ye J; Qi GF; Hong LZ; Wang F; Liu SY; Jiang Y
    Front Endocrinol (Lausanne); 2022; 13():1004913. PubMed ID: 36387877
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Machine learning-assisted decision-support models to better predict patients with calculous pyonephrosis.
    Liu H; Wang X; Tang K; Peng E; Xia D; Chen Z
    Transl Androl Urol; 2021 Feb; 10(2):710-723. PubMed ID: 33718073
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Predicting adverse drug events in older inpatients: a machine learning study.
    Hu Q; Wu B; Wu J; Xu T
    Int J Clin Pharm; 2022 Dec; 44(6):1304-1311. PubMed ID: 36115909
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Whole-tumor 3D volumetric MRI-based radiomics approach for distinguishing between benign and malignant soft tissue tumors.
    Fields BKK; Demirjian NL; Hwang DH; Varghese BA; Cen SY; Lei X; Desai B; Duddalwar V; Matcuk GR
    Eur Radiol; 2021 Nov; 31(11):8522-8535. PubMed ID: 33893534
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Identification of diagnostic and prognostic signatures derived from preoperative blood parameters for oral squamous cell carcinoma.
    Wu X; Yao Y; Dai Y; Diao P; Zhang Y; Zhang P; Li S; Jiang H; Cheng J
    Ann Transl Med; 2021 Aug; 9(15):1220. PubMed ID: 34532357
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Development and validation of a machine learning model for bone metastasis in prostate cancer: Based on inflammatory and nutritional indicators.
    Jin T; An J; Wu W; Zhou F
    Urology; 2024 May; ():. PubMed ID: 38825085
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Assessment and quantification of ovarian reserve on the basis of machine learning models.
    Ding T; Ren W; Wang T; Han Y; Ma W; Wang M; Fu F; Li Y; Wang S
    Front Endocrinol (Lausanne); 2023; 14():1087429. PubMed ID: 37008906
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Application of machine learning with multiparametric dual-energy computed tomography of the breast to differentiate between benign and malignant lesions.
    Lan X; Wang X; Qi J; Chen H; Zeng X; Shi J; Liu D; Shen H; Zhang J
    Quant Imaging Med Surg; 2022 Jan; 12(1):810-822. PubMed ID: 34993120
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Development and performance assessment of novel machine learning models to predict pneumonia after liver transplantation.
    Chen C; Yang D; Gao S; Zhang Y; Chen L; Wang B; Mo Z; Yang Y; Hei Z; Zhou S
    Respir Res; 2021 Mar; 22(1):94. PubMed ID: 33789673
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Machine learning-based dynamic prediction of lateral lymph node metastasis in patients with papillary thyroid cancer.
    Lai SW; Fan YL; Zhu YH; Zhang F; Guo Z; Wang B; Wan Z; Liu PL; Yu N; Qin HD
    Front Endocrinol (Lausanne); 2022; 13():1019037. PubMed ID: 36299455
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Development of a machine learning-based risk prediction model for cerebral infarction and comparison with nomogram model.
    Li X; Wang Y; Xu J
    J Affect Disord; 2022 Oct; 314():341-348. PubMed ID: 35882300
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.
    Zhu J; Zheng J; Li L; Huang R; Ren H; Wang D; Dai Z; Su X
    Front Med (Lausanne); 2021; 8():635771. PubMed ID: 33768105
    [No Abstract]   [Full Text] [Related]  

  • 35. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
    Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
    Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Machine learning is an effective method to predict the 90-day prognosis of patients with transient ischemic attack and minor stroke.
    Chen SD; You J; Yang XM; Gu HQ; Huang XY; Liu H; Feng JF; Jiang Y; Wang YJ
    BMC Med Res Methodol; 2022 Jul; 22(1):195. PubMed ID: 35842606
    [TBL] [Abstract][Full Text] [Related]  

  • 37. The value of hemoglobin-to-red blood cell distribution width ratio (Hb/RDW), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) for the diagnosis of nasopharyngeal cancer.
    Lin Z; Zhang X; Luo Y; Chen Y; Yuan Y
    Medicine (Baltimore); 2021 Jul; 100(28):e26537. PubMed ID: 34260530
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A Machine Learning Algorithm for Predicting the Risk of Developing to M1b Stage of Patients With Germ Cell Testicular Cancer.
    Ding L; Wang K; Zhang C; Zhang Y; Wang K; Li W; Wang J
    Front Public Health; 2022; 10():916513. PubMed ID: 35844840
    [TBL] [Abstract][Full Text] [Related]  

  • 39. [Comparison of machine learning and Logistic regression model in predicting acute kidney injury after cardiac surgery: data analysis based on MIMIC-III database].
    Xiong W; Zhang L; She K; Xu G; Bai S; Liu X
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2022 Nov; 34(11):1188-1193. PubMed ID: 36567564
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
    Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
    BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
    [TBL] [Abstract][Full Text] [Related]  

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