Bioprinting of Patient-Derived Organoids for Predicting Cancer Therapy Responses.
Sign Up to like & getrecommendations! Published in 2022 at "Advanced healthcare materials"
DOI: 10.1002/adhm.202102784
Abstract: Cancer models. This article is protected by copyright. All rights reserved. read more here.
Keywords: cancer; predicting cancer; organoids predicting; derived organoids ... See more keywords
Predicting Cancer Drug Response using a Recommender System
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DOI: 10.1093/bioinformatics/bty452
Abstract: Motivation As we move toward an era of precision medicine, the ability to predict patient‐specific drug responses in cancer based on molecular information such as gene expression data represents both an opportunity and a challenge.… read more here.
Keywords: drug response; drug; cancer; predicting cancer ... See more keywords
Predicting cancer outcome: Artificial intelligence vs. pathologists.
Sign Up to like & getrecommendations! Published in 2019 at "Oral diseases"
DOI: 10.1111/odi.12954
Abstract: Determining cancer prognosis in patients is crucial to controlling the suffering and death due to cancer. In general, the diagnosis of cancer is based on the histology. Histology of cancer is determined by the tissue… read more here.
Keywords: diagnosis cancer; cancer outcome; outcome artificial; cancer ... See more keywords
A nomogram for predicting cancer-specific survival in different age groups for operable gastric cancer: a population-based study
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DOI: 10.21037/tcr.2020.02.37
Abstract: Gastric cancer (GC) is the fifth most common cancer in the world and the third leading cause of cancer-related mortality (1). Although great progress has been made in the treatment of GC, the prognosis is… read more here.
Keywords: gastric cancer; age; cancer specific; nomogram predicting ... See more keywords
Nomogram for predicting cancer-specific survival of patients with clear-cell renal cell carcinoma: a SEER-based population study.
Sign Up to like & getrecommendations! Published in 2022 at "General physiology and biophysics"
DOI: 10.4149/gpb_2022040
Abstract: This study was aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of patients with clear-cell renal cell carcinoma (ccRCC). Based on the Surveillance, Epidemiology, and End Results (SEER) database, 24,477 patients diagnosed… read more here.
Keywords: nomogram predicting; patients clear; cancer specific; specific survival ... See more keywords