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researcher

D. Higgins

4 papers hereh-index 6223 citations11 works total

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

author position
  • sole author1
  • first author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CY3
  • cs.AI1
same name
  • D. Higgins — 7 papers, h 15
  • D. Higgins — 7 papers, h 6
  • D. Higgins — 3 papers, h 2
  • D. Higgins — 2 papers, h 4
  • D. Higgins — 1 paper, h 1
  • D. Higgins — 1 paper, h 19

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
20202023
most citedFrom Bit To Bedside: A Practical Framework For Artificial Intelligence Product Development In Healthcare

116 citations · 168 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CY2023★ 30 cited

Validation of artificial intelligence containing products across the regulated healthcare industries

David Higgins, Christian Johner

Purpose: The introduction of artificial intelligence / machine learning (AI/ML) products to the regulated fields of pharmaceutical research and development (R&D) and drug manufactu…

cs.AI2021★ 7 cited

Artificial Intelligence in Healthcare: Lost In Translation?

Vince I. Madai, David C. Higgins

Artificial intelligence (AI) in healthcare is a potentially revolutionary tool to achieve improved healthcare outcomes while reducing overall health costs. While many exploratory r…

cs.CY2020★ 15 cited

OnRAMP for Regulating AI in Medical Products

David Higgins

Medical Artificial Intelligence (AI) involves the application of machine learning algorithms to biomedical datasets in order to improve medical practices. Products incorporating me…

cs.CY2020★ 116 cited

From Bit To Bedside: A Practical Framework For Artificial Intelligence Product Development In Healthcare

David Higgins, Vince I. Madai

Artificial Intelligence (AI) in healthcare holds great potential to expand access to high-quality medical care, whilst reducing overall systemic costs. Despite hitting the headline…

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