Clinical Decision-Making and Predicting Patient Trajectories

Bhat, Anup P.; Dumore, Nitin G.; Dhoble, S.J.; Rewatkar, K. G.

doi:10.1007/978-981-16-0538-3_13

Advanced Prognostic Predictive Modelling in Healthcare Data Analytics

2021

DOI: 10.1007/978-981-16-0538-3_13

|View full text |Cite

Clinical Decision-Making and Predicting Patient Trajectories

Anup P. Bhat¹,

Nitin G. Dumore²,

S.J. Dhoble

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...

Book1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

AI and Chronic Diseases From Data Integration to Clinical Implementation

Joshi

2024

Advances in Healthcare Information Systems and Administration

View full text Add to dashboard Cite

The integration of artificial intelligence (AI) into chronic disease management offers transformative potential for enhancing patient care, predictive analytics, and personalized treatment. As chronic illnesses like diabetes, cardiovascular diseases, and cancer rise globally, AI technologies—machine learning, deep learning, natural language processing—provide innovative solutions. This chapter explores AI's role in predicting health events, personalizing treatment, and optimizing outcomes through case studies and practical implementations. Ethical, privacy, and regulatory considerations are addressed to ensure AI complements human caregiving. The chapter also emphasizes global perspectives, promoting inclusive, culturally sensitive AI adoption to enhance healthcare equity and accessibility, envisioning a future where AI empowers healthcare professionals and patients.

show abstract

AI and Chronic Diseases From Data Integration to Clinical Implementation

Joshi

2024

Advances in Healthcare Information Systems and Administration

View full text Add to dashboard Cite

show abstract

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

customersupport@researchsolutions.com

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

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

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.

Clinical Decision-Making and Predicting Patient Trajectories

Cited by 1 publication

References 38 publications

AI and Chronic Diseases From Data Integration to Clinical Implementation

AI and Chronic Diseases From Data Integration to Clinical Implementation

Contact Info

Product

Resources

About