Integrative analysis of multimodal patient data identifies personalized predictors of tuberculosis treatment prognosis

Sambarey, Awanti; Smith, Kirk; Chung, Carolina; Arora, Harkirat Singh; Yang, Zhenhua; Agarwal, Prachi P.; Chandrasekaran, Sriram

doi:10.1016/j.isci.2024.109025

iScience

2024

DOI: 10.1016/j.isci.2024.109025

|View full text |Cite

Integrative analysis of multimodal patient data identifies personalized predictors of tuberculosis treatment prognosis

Awanti Sambarey,

Kirk Smith,

Carolina Chung

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 53 publications

(63 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?

Sun,

Macedonia,

Chen

et al. 2024

J. Med. Chem.

View full text Add to dashboard Cite

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?

Sun,

Macedonia,

Chen

et al. 2024

J. Med. Chem.

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Integrative analysis of multimodal patient data identifies personalized predictors of tuberculosis treatment prognosis

Cited by 1 publication

References 53 publications

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?

Contact Info

Product

Resources

About