Spatial omics-based machine learning algorithms for the early detection of hepatocellular carcinoma
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
Spatial omics-based machine learning algorithms for the early detection of hepatocellular carcinoma ; volume:4 ; number:1 ; day:3 ; month:12 ; year:2024 ; pages:1-11 ; date:12.2024
Communications medicine ; 4, Heft 1 (3.12.2024), 1-11, 12.2024
- Creator
-
Wang, Mengjun
Grauzam, Stephane
Bayram, Muhammed Furkan
Dressman, James
DelaCourt, Andrew
Blaschke, Calvin
Liang, Hongyan
Scott, Danielle
Huffman, Gray
Black, Alyson
Ochoa-Rios, Shaaron
Lewin, David
Angel, Peggi M.
Drake, Richard R.
Ball, Lauren
Bethard, Jennifer
Castellino, Stephen
Kono, Yuko
Kubota, Naoto
Hoshida, Yujin
Quirk, Lisa
Yopp, Adam
Gopal, Purva
Singal, Amit
Mehta, Anand S.
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1038/s43856-024-00677-7
- URN
-
urn:nbn:de:101:1-2502172227251.529746443257
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:36 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Wang, Mengjun
- Grauzam, Stephane
- Bayram, Muhammed Furkan
- Dressman, James
- DelaCourt, Andrew
- Blaschke, Calvin
- Liang, Hongyan
- Scott, Danielle
- Huffman, Gray
- Black, Alyson
- Ochoa-Rios, Shaaron
- Lewin, David
- Angel, Peggi M.
- Drake, Richard R.
- Ball, Lauren
- Bethard, Jennifer
- Castellino, Stephen
- Kono, Yuko
- Kubota, Naoto
- Hoshida, Yujin
- Quirk, Lisa
- Yopp, Adam
- Gopal, Purva
- Singal, Amit
- Mehta, Anand S.
- SpringerLink (Online service)
Other Objects (12)
Spatial recall index for machine learning algorithms
Feature reduction for hepatocellular carcinoma prediction using machine learning algorithms
Multi-omics in prognosis of hepatocellular carcinoma
Deciphering spatial domains from spatial multi-omics with SpatialGlue
Enhancing spatial streamflow prediction through machine learning algorithms and advanced strategies
Single cell-spatial transcriptomics and bulk multi-omics analysis of heterogeneity and ecosystems in hepatocellular carcinoma
Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms
DNA‐Barcoded Fluorescence Microscopy for Spatial Omics
SPATIAL DOWNSCALING OF GPM IMERG V06 GRIDDED PRECIPITATION USING MACHINE LEARNING ALGORITHMS
G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma
SpatialData: an open and universal data framework for spatial omics
Enhancing spatial resolution in Fourier transform infrared spectral image via machine learning algorithms
Spatial recall index for machine learning algorithms
Feature reduction for hepatocellular carcinoma prediction using machine learning algorithms
Multi-omics in prognosis of hepatocellular carcinoma
Deciphering spatial domains from spatial multi-omics with SpatialGlue
Enhancing spatial streamflow prediction through machine learning algorithms and advanced strategies
Single cell-spatial transcriptomics and bulk multi-omics analysis of heterogeneity and ecosystems in hepatocellular carcinoma
Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms
DNA‐Barcoded Fluorescence Microscopy for Spatial Omics
SPATIAL DOWNSCALING OF GPM IMERG V06 GRIDDED PRECIPITATION USING MACHINE LEARNING ALGORITHMS
G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma
SpatialData: an open and universal data framework for spatial omics
Enhancing spatial resolution in Fourier transform infrared spectral image via machine learning algorithms
Spatial recall index for machine learning algorithms
Feature reduction for hepatocellular carcinoma prediction using machine learning algorithms
Multi-omics in prognosis of hepatocellular carcinoma
Deciphering spatial domains from spatial multi-omics with SpatialGlue
Enhancing spatial streamflow prediction through machine learning algorithms and advanced strategies
Single cell-spatial transcriptomics and bulk multi-omics analysis of heterogeneity and ecosystems in hepatocellular carcinoma
Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms
DNA‐Barcoded Fluorescence Microscopy for Spatial Omics
SPATIAL DOWNSCALING OF GPM IMERG V06 GRIDDED PRECIPITATION USING MACHINE LEARNING ALGORITHMS
G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma
SpatialData: an open and universal data framework for spatial omics