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researcher

Thomas Kannampallil

2 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.CL1
  • cs.LG1
ORCID 0000-0003-4119-4836

identity via Semantic Scholar / OpenAlex

most citedA Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients

8 citations · 8 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024★ 8 cited

A Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients

Junbo Shen, Bing Xue, Thomas Kannampallil +2

Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for…

cs.CL2023

Utilizing Semantic Textual Similarity for Clinical Survey Data Feature Selection

Benjamin C. Warner, Ziqi Xu, Simon Haroutounian +2

Survey data can contain a high number of features while having a comparatively low quantity of examples. Machine learning models that attempt to predict outcomes from survey data u…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.