Scholarly Production and Public Health Determinants in Context of Funding: The Case of IoMT Research:

• URL: http://arxiv.org/abs/2606.22411v1
• Date: Sun, 21 Jun 2026 09:56:30 GMT
• Title: Scholarly Production and Public Health Determinants in Context of Funding: The Case of IoMT Research:
• Abstract summary: The Internet of Medical Things (IoMT) represents a transformative technology that connects medical devices, sensors, and healthcare systems.<n>The scale and scope of research funding and their influence on research literature production patterns and country health determinants remain unknown.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The Internet of Medical Things (IoMT) represents a transformative technology that connects medical devices, sensors, and healthcare systems to enable real-time monitoring, data sharing, and advanced decision-making in healthcare. While the technical and clinical potential of IoMT has been researched extensively, the scale and scope of research funding and their influence on research literature production patterns and country health determinants remain unknown. The study presented in this paper covers this gap by employing triangulation of quantitative and qualitative approaches. The results reveal a positive trend IoMT in research literature produc-tion. Thematic analysis shows that both funded and non-funded are associated with similar themes; however, founded research is more focused on recent research trends like artificial in-telligence applications in healthcare. Finally, our study revealed the positive association be-tween the number of funded papers and health determinants, suggesting that IoMT research funding might contribute to improved healthcare delivery.

Related papers

• An Analysis of Artificial Intelligence Adoption in NIH-Funded Research [2.5782420501870296]
  We present a comprehensive analysis of 58,746 NIH-funded biomedical research projects from 2025.<n>We show that AI constitutes 15.9% of the NIH portfolio with a 13.4% funding premium.<n>Health disparities research is severely underrepresented at just 5.7% of AI-funded work.
  arXiv  Detail & Related papers  (2026-04-08T17:05:11Z)
• Towards a Medical AI Scientist [73.6056699962416]
  We introduce Medical AI Scientist, the first autonomous research framework tailored to clinical autonomous research.<n>The framework operates under 3 research modes, namely paper-based reproduction, literature-inspired innovation, and task-driven exploration.<n>Our system achieves strong alignment between the proposed method and its implementation, while also demonstrating significantly higher success rates in executable experiments.
  arXiv  Detail & Related papers  (2026-03-30T15:37:25Z)
• Global research trends and collaborations in Fibrodysplasia Ossificans Progressiva: A bibliometric analysis (1989-2023) [0.27528170226206433]
  Fibrodysplasia Ossificans Progressiva (FOP) is a rare and debilitating genetic disorder.<n>This scientometric analysis examines the global research trends on FOP between 1989 and 2023 using data from Web of Science.<n>The study highlights key patterns in publication productivity, influential journals, institutions, and the geographical distribution of research.
  arXiv  Detail & Related papers  (2026-01-07T06:17:04Z)
• The Role of Computing Resources in Publishing Foundation Model Research [84.20094600030092]
  We evaluate the relationship between these resources and the scientific advancement of foundation models (FM)<n>We reviewed 6517 FM papers published between 2022 to 2024, and surveyed 229 first-authors to the impact of computing resources on scientific output.<n>We find that increased computing is correlated with national funding allocations and citations, but our findings don't observe the strong correlations with research environment.
  arXiv  Detail & Related papers  (2025-10-15T14:50:45Z)
• Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications [59.721265428780946]
  Large Language Models (LLMs) in medicine have enabled impressive capabilities, yet a critical gap remains in their ability to perform systematic, transparent, and verifiable reasoning.<n>This paper provides the first systematic review of this emerging field.<n>We propose a taxonomy of reasoning enhancement techniques, categorized into training-time strategies and test-time mechanisms.
  arXiv  Detail & Related papers  (2025-08-01T14:41:31Z)
• Rapid Biomedical Research Classification: The Pandemic PACT Advanced Categorisation Engine [10.692728349388297]
  Pandemic PACT project aims to track and analyse research funding and clinical evidence for a wide range of diseases with outbreak potential. This paper introduces the Pandemic PACT Advanced Categorisation Engine (PPACE) along with its associated dataset.
  arXiv  Detail & Related papers  (2024-07-14T05:22:53Z)
• Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis [24.532570258954898]
  Large Language Models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI) This study aims to provide a comprehensive overview of LLM applications in BHI, highlighting their transformative potential and addressing the associated ethical and practical challenges.
  arXiv  Detail & Related papers  (2024-03-24T21:29:39Z)
• De-identification of clinical free text using natural language processing: A systematic review of current approaches [48.343430343213896]
  Natural language processing has repeatedly demonstrated its feasibility in automating the de-identification process. Our study aims to provide systematic evidence on how the de-identification of clinical free text has evolved in the last thirteen years.
  arXiv  Detail & Related papers  (2023-11-28T13:20:41Z)
• Semi-automated extraction of research topics and trends from NCI funding in radiological sciences from 2000-2020 [0.0]
  We developed a semi-automated approach to extract and name research topics. We applied this to $1.9B of NCI funding over 21 years in the radiological sciences.
  arXiv  Detail & Related papers  (2023-06-22T17:47:42Z)
• A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises [59.4999994297993]
  This comprehensive review aims to provide an overview of the current state of Healthcare Knowledge Graphs (HKGs)<n>We thoroughly analyzed existing literature on HKGs, covering their construction methodologies, utilization techniques, and applications.<n>The review highlights the potential of HKGs to significantly impact biomedical research and clinical practice.
  arXiv  Detail & Related papers  (2023-06-07T21:51:56Z)
• Machine Learning Applications for Therapeutic Tasks with Genomics Data [49.98249191161107]
  We review the literature on machine learning applications for genomics through the lens of therapeutic development. We identify twenty-two machine learning in genomics applications across the entire therapeutics pipeline. We pinpoint seven important challenges in this field with opportunities for expansion and impact.
  arXiv  Detail & Related papers  (2021-05-03T21:20:20Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.