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researcher

B. Chakraborty

13 papers hereh-index 263.1k citations116 works total

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

author position
  • middle author5
  • last author7

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • stat.ME7
  • cs.LG3
  • stat.AP2
  • stat.ML1
same name
  • B. Chakraborty — 70 papers, h 28
  • B. Chakraborty — 54 papers, h 15
  • B. Chakraborty — 31 papers, h 6
  • B. Chakraborty — 20 papers, h 14
  • B. Chakraborty — 13 papers, h 15
  • B. Chakraborty — 3 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172022
most citedDeep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

160 citations · 246 across the 13 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2021★ 160 cited

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

Feng Xie, Han Yuan, Yilin Ning +5

Objective: Temporal electronic health records (EHRs) can be a wealth of information for secondary uses, such as clinical events prediction or chronic disease management. However, c…

cs.LG2021★ 21 cited

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data

Han Yuan, Feng Xie, Marcus Eng Hock Ong +7

Background: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among a wide variety of decision-making models for determining the…

cs.LG2021★ 30 cited

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data

Feng Xie, Yilin Ning, Han Yuan +4

Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created…

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