Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/1989
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dc.contributor.authorMalhotra, Chehak-
dc.contributor.authorGopal, Mehak-
dc.contributor.authorSethi, Tavpritesh (Advisor)-
dc.date.accessioned2026-06-17T10:39:57Z-
dc.date.available2026-06-17T10:39:57Z-
dc.date.issued2024-01-
dc.identifier.urihttp://repository.iiitd.edu.in/xmlui/handle/123456789/1989-
dc.description.abstractThis study encapsulates our progress in the integration of advanced AI models within healthcare contexts. Utilizing state-of-the-art models for new tasks, we explore their efficacy in tasks like cancer classification and shock prediction using data from clinical notes and prescriptions. Our study underscores the potential of AI to revolutionize healthcare practices and improve patient outcomes.en_US
dc.language.isoen_USen_US
dc.publisherIIIT-Delhien_US
dc.subjectPatient Diagnosisen_US
dc.subjectCancer classificationen_US
dc.subjectAI in Healthcareen_US
dc.titleAI/ML in healthcare: leveraging embeddings for patient diagnosis and treatment optimizationen_US
dc.typeOtheren_US
Appears in Collections:Year-2024

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