Your browser doesn't support javascript.
loading
Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder.
Bartsch, Georg; Mitra, Anirban P; Mitra, Sheetal A; Almal, Arpit A; Steven, Kenneth E; Skinner, Donald G; Fry, David W; Lenehan, Peter F; Worzel, William P; Cote, Richard J.
Affiliation
  • Bartsch G; University of Southern California, Los Angeles, California; Goethe University Frankfurt, Frankfurt, Germany.
  • Mitra AP; University of Southern California, Los Angeles, California.
  • Mitra SA; University of Southern California, Los Angeles, California.
  • Almal AA; Everist Genomics, Ann Arbor, Michigan.
  • Steven KE; University of Copenhagen, Copenhagen, Denmark.
  • Skinner DG; University of Southern California, Los Angeles, California.
  • Fry DW; Everist Genomics, Ann Arbor, Michigan.
  • Lenehan PF; Everist Genomics, Ann Arbor, Michigan.
  • Worzel WP; Everist Genomics, Ann Arbor, Michigan.
  • Cote RJ; University of Miami, Miami, Florida. Electronic address: RCote@med.miami.edu.
J Urol ; 195(2): 493-8, 2016 Feb.
Article in En | MEDLINE | ID: mdl-26459038
Subject(s)
Key words
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Urinary Bladder Neoplasms / Artificial Intelligence / Carcinoma, Transitional Cell / Gene Expression Profiling / Neoplasm Invasiveness Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male Language: En Journal: J Urol Year: 2016 Document type: Article Affiliation country: Germany
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Urinary Bladder Neoplasms / Artificial Intelligence / Carcinoma, Transitional Cell / Gene Expression Profiling / Neoplasm Invasiveness Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male Language: En Journal: J Urol Year: 2016 Document type: Article Affiliation country: Germany