This paper is in the following e-collection/theme issue:

Artificial Intelligence (1371) Digital Health Reviews (1289) Decision Support for Health Professionals (1185) Machine Learning (1465) Imaging Informatics (193) Clinical Information and Decision Making (1407) Innovations and Technology in Cancer Care (423) Prostate Cancer (26)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22394, first published .
Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review

Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review

Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review

Authors of this article:

Rossana Castaldo1 Author Orcid Image ;   Carlo Cavaliere1 Author Orcid Image ;   Andrea Soricelli1 Author Orcid Image ;   Marco Salvatore1 Author Orcid Image ;   Leandro Pecchia2 Author Orcid Image ;   Monica Franzese1 Author Orcid Image
Article Authors Cited by (27) Tweetations (14) Metrics

Journals

  1. Lasorsa F, di Meo N, Rutigliano M, Ferro M, Terracciano D, Tataru O, Battaglia M, Ditonno P, Lucarelli G. Emerging Hallmarks of Metabolic Reprogramming in Prostate Cancer. International Journal of Molecular Sciences 2023;24(2):910 View
  2. Chen T, Zhang Z, Tan S, Zhang Y, Wei C, Wang S, Zhao W, Qian X, Zhou Z, Shen J, Dai Y, Hu J. MRI Based Radiomics Compared With the PI-RADS V2.1 in the Prediction of Clinically Significant Prostate Cancer: Biparametric vs Multiparametric MRI. Frontiers in Oncology 2022;11 View
  3. Yu C, Wang J. Data mining and mathematical models in cancer prognosis and prediction. Medical Review 2022;2(3):285 View
  4. Infante T, Cavaliere C, Punzo B, Grimaldi V, Salvatore M, Napoli C. Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review. Circulation: Cardiovascular Imaging 2021;14(12):1133 View
  5. Xiong Y, Ma Y, Ruan L, Li D, Lu C, Huang L. Comparing different machine learning techniques for predicting COVID-19 severity. Infectious Diseases of Poverty 2022;11(1) View
  6. Ferro M, de Cobelli O, Musi G, del Giudice F, Carrieri G, Busetto G, Falagario U, Sciarra A, Maggi M, Crocetto F, Barone B, Caputo V, Marchioni M, Lucarelli G, Imbimbo C, Mistretta F, Luzzago S, Vartolomei M, Cormio L, Autorino R, Tătaru O. Radiomics in prostate cancer: an up-to-date review. Therapeutic Advances in Urology 2022;14 View
  7. Reginelli A, Nardone V, Giacobbe G, Belfiore M, Grassi R, Schettino F, Del Canto M, Grassi R, Cappabianca S. Radiomics as a New Frontier of Imaging for Cancer Prognosis: A Narrative Review. Diagnostics 2021;11(10):1796 View
  8. Castillo T. J, Arif M, Starmans M, Niessen W, Bangma C, Schoots I, Veenland J. Classification of Clinically Significant Prostate Cancer on Multi-Parametric MRI: A Validation Study Comparing Deep Learning and Radiomics. Cancers 2021;14(1):12 View
  9. Pane K, Zanfardino M, Grimaldi A, Baldassarre G, Salvatore M, Incoronato M, Franzese M. Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB. Biomedicines 2022;10(6):1306 View
  10. Oh J, Hong S. Polygenic risk score in prostate cancer. Current Opinion in Urology 2022;32(5):466 View
  11. Castaldo R, Brancato V, Cavaliere C, Trama F, Illiano E, Costantini E, Ragozzino A, Salvatore M, Nicolai E, Franzese M. A Framework of Analysis to Facilitate the Harmonization of Multicenter Radiomic Features in Prostate Cancer. Journal of Clinical Medicine 2022;12(1):140 View
  12. Pirrone G, Matrone F, Chiovati P, Manente S, Drigo A, Donofrio A, Cappelletto C, Borsatti E, Dassie A, Bortolus R, Avanzo M. Predicting Local Failure after Partial Prostate Re-Irradiation Using a Dosiomic-Based Machine Learning Model. Journal of Personalized Medicine 2022;12(9):1491 View
  13. EMAM Z, ADA E. A Synopsis of Machine and Deep Learning in Medical Physics and Radiology. Journal of Basic and Clinical Health Sciences 2022;6(3):946 View
  14. Duan B, Lv H, Huang Y, Xu Z, Chen W. Deep learning for the screening of primary ciliary dyskinesia based on cranial computed tomography. Frontiers in Physiology 2023;14 View
  15. Paliwal A, Faust K, Alshoumer A, Diamandis P. Standardizing analysis of intra‐tumoral heterogeneity with computational pathology. Genes, Chromosomes and Cancer 2023;62(9):526 View
  16. Kolasa K, Admassu B, Hołownia-Voloskova M, Kędzior K, Poirrier J, Perni S. Systematic reviews of machine learning in healthcare: a literature review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(1):63 View
  17. Zhong J, Lu J, Zhang G, Mao S, Chen H, Yin Q, Hu Y, Xing Y, Ding D, Ge X, Zhang H, Yao W. An overview of meta-analyses on radiomics: more evidence is needed to support clinical translation. Insights into Imaging 2023;14(1) View
  18. Huynh L, Bonebrake B, Tran J, Marasco J, Ahlering T, Wang S, Baine M. Multi-Institutional Development and Validation of a Radiomic Model to Predict Prostate Cancer Recurrence Following Radical Prostatectomy. Journal of Clinical Medicine 2023;12(23):7322 View
  19. Chen J, Feng B, Hu M, Huang F, Chen Y, Ma X, Long W. A transfer learning nomogram for predicting prostate cancer and benign conditions on MRI. BMC Medical Imaging 2023;23(1) View
  20. Gao L, Kyubwa E, Starbird M, Diaz de Leon J, Nguyen M, Rogers C, Menon N. Circulating miRNA profiles in COVID-19 patients and meta-analysis: implications for disease progression and prognosis. Scientific Reports 2023;13(1) View
  21. 张 皓. The Application of Artificial Intelligence in PSMA PET/CT. Advances in Clinical Medicine 2024;14(01):1501 View
  22. Ruan M, Liu Y, Yao K, Wang K, Fan Y, Wu S, Wang X. Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI‐RADS v2.1 Score ≥3. Journal of Magnetic Resonance Imaging 2024 View
  23. Zhang H, Qi L, Cai Y, Gao X. Gastrin-releasing peptide receptor (GRPR) as a novel biomarker and therapeutic target in prostate cancer. Annals of Medicine 2024;56(1) View
  24. Gunda S, Yip J, Ng V, Chen Z, Han X, Chen X, Pang M, Ying M. The Diagnostic Accuracy of Transcranial Color-Coded Doppler Ultrasound Technique in Stratifying Intracranial Cerebral Artery Stenoses in Cerebrovascular Disease Patients: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine 2024;13(5):1507 View
  25. Li Q, Wang Y, Chen J, Zeng K, Wang C, Guo X, Hu Z, Hu J, Liu B, Xiao J, Zhou P. Machine learning based androgen receptor regulatory gene-related random forest survival model for precise treatment decision in prostate cancer. Heliyon 2024;10(17):e37256 View
  26. Huang F, Huang Q, Liao X, Gao Y. Prediction of high-risk prostate cancer based on the habitat features of biparametric magnetic resonance and the omics features of contrast-enhanced ultrasound. Heliyon 2024;10(18):e37955 View

Books/Policy Documents

  1. Saghazadeh A, Rezaei N. Handbook of Cancer and Immunology. View