Mining comorbidities of opioid use disorder from FDA adverse event reporting system and patient electronic health records
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1472-6947
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Mining comorbidities of opioid use disorder from FDA adverse event reporting system and patient electronic health records ; volume:22 ; number:2 ; day:16 ; month:6 ; year:2022 ; pages:1-11 ; date:12.2022
BMC medical informatics and decision making ; 22, Heft 2 (16.6.2022), 1-11, 12.2022
- Urheber
-
Pan, Yiheng
Xu, Rong
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s12911-022-01869-8
- URN
-
urn:nbn:de:101:1-2022081021594516037409
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:24 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Pan, Yiheng
- Xu, Rong
- SpringerLink (Online service)
Ähnliche Objekte (12)
Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection
Data-driven multiple-level analysis of gut-microbiome-immune-joint interactions in rheumatoid arthritis
Large-scale mining disease comorbidity relationships from post-market drug adverse events surveillance data
Towards understanding brain-gut-microbiome connections in Alzheimer’s disease
A genomics-based systems approach towards drug repositioning for rheumatoid arthritis
Context-sensitive network analysis identifies food metabolites associated with Alzheimer’s disease: an exploratory study
Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing
Phenome-based gene discovery provides information about Parkinson’s disease drug targets
The horizontal-to-vertical spectral ratio and its applications
dRiskKB: a large-scale disease-disease risk relationship knowledge base constructed from biomedical text
Predict Alzheimer’s disease using hippocampus MRI data: a lightweight 3D deep convolutional network model with visual and global shape representations
Mean corpuscular hemoglobin predicts the length of hospital stay independent of severity classification in patients with acute pancreatitis
Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection
Data-driven multiple-level analysis of gut-microbiome-immune-joint interactions in rheumatoid arthritis
Large-scale mining disease comorbidity relationships from post-market drug adverse events surveillance data
Towards understanding brain-gut-microbiome connections in Alzheimer’s disease
A genomics-based systems approach towards drug repositioning for rheumatoid arthritis
Context-sensitive network analysis identifies food metabolites associated with Alzheimer’s disease: an exploratory study
Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing
Phenome-based gene discovery provides information about Parkinson’s disease drug targets
The horizontal-to-vertical spectral ratio and its applications
dRiskKB: a large-scale disease-disease risk relationship knowledge base constructed from biomedical text
Predict Alzheimer’s disease using hippocampus MRI data: a lightweight 3D deep convolutional network model with visual and global shape representations
Mean corpuscular hemoglobin predicts the length of hospital stay independent of severity classification in patients with acute pancreatitis
Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection
Data-driven multiple-level analysis of gut-microbiome-immune-joint interactions in rheumatoid arthritis
Large-scale mining disease comorbidity relationships from post-market drug adverse events surveillance data
Towards understanding brain-gut-microbiome connections in Alzheimer’s disease
A genomics-based systems approach towards drug repositioning for rheumatoid arthritis
Context-sensitive network analysis identifies food metabolites associated with Alzheimer’s disease: an exploratory study
Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing
Phenome-based gene discovery provides information about Parkinson’s disease drug targets
The horizontal-to-vertical spectral ratio and its applications
dRiskKB: a large-scale disease-disease risk relationship knowledge base constructed from biomedical text
Predict Alzheimer’s disease using hippocampus MRI data: a lightweight 3D deep convolutional network model with visual and global shape representations