Work

Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy

Year: 2010

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-642-15711-0_83

Authors: Pallavi Tiwari, John Kurhanewicz, Mark Rosen, Anant Madabhushi

Institutions: Rutgers, The State University of New Jersey, University of California, San Francisco, University of Pennsylvania

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: U.S. Department of Defense, Rutgers Cancer Institute of New Jersey, National Cancer Institute

Awards: Detecting pre-cancerous lesions from high resolution prostate MRI, G393240631, G4119534169, G4837765142, G916986889, G961828503

OpenAlex ID: W1613739536

FWCI: 13.85

Cites: 13

Cited by: 34

Related to: 10