A study to evaluate the implications of cost burden on antimicrobial resistance AMR using data analytics techniques

dc.contributor.guide	Rajesh, V.,Vandana, K E and Surulivel, Rajan M
dc.coverage.spatial	Pharmaceutics
dc.creator.researcher	Prashant Chandra
dc.date.accessioned	2023-10-04T09:10:09Z
dc.date.available	2023-10-04T09:10:09Z
dc.date.awarded	2023
dc.date.completed	2023
dc.date.registered	2019
dc.description.abstract	Available newline
dc.description.note	Bibliography p.109-117
dc.format.accompanyingmaterial	None
dc.format.dimensions	-
dc.format.extent	118p.
dc.identifier.uri	http://hdl.handle.net/10603/515892
dc.language	English
dc.publisher.institution	Manipal College of Pharmaceutical Sciences
dc.publisher.place	Manipal
dc.publisher.university	Manipal Academy of Higher Education
dc.relation	No. of References 100
dc.rights	university
dc.source.university	University
dc.subject.keyword	Antimicrobial resistance, Hospital-acquired infections
dc.subject.keyword	COVID-19, ATC/DDDs index
dc.subject.keyword	Length of stay, Health care cost Mortality
dc.subject.keyword	Machine learning algorithms, Healthcare cost
dc.title	A study to evaluate the implications of cost burden on antimicrobial resistance AMR using data analytics techniques
dc.title.alternative	-
dc.type.degree	Ph.D.