Please use this identifier to cite or link to this item:
http://repository.iiitd.edu.in/xmlui/handle/123456789/1989Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Malhotra, Chehak | - |
| dc.contributor.author | Gopal, Mehak | - |
| dc.contributor.author | Sethi, Tavpritesh (Advisor) | - |
| dc.date.accessioned | 2026-06-17T10:39:57Z | - |
| dc.date.available | 2026-06-17T10:39:57Z | - |
| dc.date.issued | 2024-01 | - |
| dc.identifier.uri | http://repository.iiitd.edu.in/xmlui/handle/123456789/1989 | - |
| dc.description.abstract | This 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.iso | en_US | en_US |
| dc.publisher | IIIT-Delhi | en_US |
| dc.subject | Patient Diagnosis | en_US |
| dc.subject | Cancer classification | en_US |
| dc.subject | AI in Healthcare | en_US |
| dc.title | AI/ML in healthcare: leveraging embeddings for patient diagnosis and treatment optimization | en_US |
| dc.type | Other | en_US |
| Appears in Collections: | Year-2024 | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| BTP_Report (2) - Chehak Malhotra.pdf Restricted Access | 1.59 MB | Adobe PDF | View/Open Request a copy |
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