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Muhammad Bilal

12 papers hereh-index 331 citations21 works total

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

author position
  • first author2
  • middle author5
  • last author1

Across the 8 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.CL2
  • cs.LG1
  • eess.IV1
same name
  • Muhammad Bilal — 11 papers, h 14
  • Muhammad Bilal — 5 papers, h 2
  • Muhammad Bilal — 4 papers, h 5
  • Muhammad Bilal — 4 papers, h 2
  • Muhammad Bilal — 3 papers, h 4
  • Muhammad Bilal — 3 papers, h 1

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
20232026
most citedOpen Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription

3 citations · 6 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

3 papers · 1 filter

cs.CV2025

TEMSET-24K: Densely Annotated Dataset for Indexing Multipart Endoscopic Videos using Surgical Timeline Segmentation

Muhammad Bilal, Mahmood Alam, Deepa Bapu +16

Indexing endoscopic surgical videos is vital in surgical data science, forming the basis for systematic retrospective analysis and clinical performance evaluation. Despite its sign…

cs.CL2025★ 3 cited

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription

Mahdi Alkaeed, Sofiat Abioye, Adnan Qayyum +7

In response to the success of proprietary Large Language Models (LLMs), there is a growing interest in developing open, non-proprietary LLMs and AI foundation models (AIFMs) for tr…

cs.CV2025

Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review

Ufaq Khan, Umair Nawaz, Adnan Qayyum +5

Recent advancements in machine learning (ML) and deep learning (DL), particularly through the introduction of Foundation Models (FMs), have significantly enhanced surgical scene un…

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