John Ioannidis and co-authors [1] created a publicly available database of top-cited scientists in the world. This database, intended to address the misuse of citation metrics, has generated a lot of interest among the scientific community, institutions, and media. Many institutions used this as a yardstick to assess the quality of researchers. At the same time, some people look at this list with skepticism citing problems with the methodology used. Two separate databases are created based on career-long and, single recent year impact. This database is created using Scopus data from Elsevier[1-3]. The Scientists included in this database are classified into 22 scientific fields and 174 sub-fields. The parameters considered for this analysis are total citations from 1996 to 2022 (nc9622), h index in 2022 (h22), c-score, and world rank based on c-score (Rank ns). Citations without self-cites are considered in all cases (indicated as ns). In the case of a single-year case, citations during 2022 (nc2222) instead of Nc9622 are considered.

To evaluate the robustness of c-score-based ranking, I have done a detailed analysis of the matrix parameters of the last 25 years (1998-2022) of Nobel laureates of Physics, chemistry, and medicine, and compared them with the top 100 rank holders in the list. The latest career-long and single-year-based databases (2022) were used for this analysis. The details of the analysis are presented below: Though the article says the selection is based on the top 100,000 scientists by c-score (with and without self-citations) or a percentile rank of 2% or above in the sub-field, the actual career-based ranking list has 204644 names[1]. The single-year database contains 210199 names. So, the list published contains ~ the top 4% of scientists. In the career-based rank list, for the person with the lowest rank of 4809825, the nc9622, h22, and c-score were 41, 3, and 1.3632, respectively. Whereas for the person with the No.1 rank in the list, the nc9622, h22, and c-score were 345061, 264, and 5.5927, respectively. Three people on the list had less than 100 citations during 96-2022, 1155 people had an h22 less than 10, and 6 people had a C-score less than 2.
In the single year-based rank list, for the person with the lowest rank (6547764), the nc2222, h22, and c-score were 1, 1, and 0. 6, respectively. Whereas for the person with the No.1 rank, the nc9622, h22, and c-score were 34582, 68, and 5.3368, respectively. 4463 people on the list had less than 100 citations in 2022, 71512 people had an h22 less than 10, and 313 people had a C-score less than 2. The entry of many authors having single digit H index and a very meager total number of citations indicates serious shortcomings of the c-score-based ranking methodology. These results indicate shortcomings in the ranking methodology.

Abstract

Master Beneficiary Summary Files (MBSF)

Usage

This dataset page includes some of the tables from the Medicare Data in PHS's possession. Other Medicare tables are included on other dataset pages on the PHS Data Portal. Depending upon your research question and your DUA with CMS, you may only need tables from a subset of the Medicare dataset pages, or you may need tables from all of them.

The location of each of the Medicare tables (i.e. a chart of which tables are included in each Medicare dataset page) is shown here.

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https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Documentation

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Section 2

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Usage Notes

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The global market for integrated medicine and engineering education is experiencing robust growth, projected at a compound annual growth rate (CAGR) of 8% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing demand for healthcare professionals skilled in both medical science and engineering principles is fueling the need for specialized programs. Advances in medical technology, such as robotics, AI, and bioprinting, require professionals with a holistic understanding of both engineering design and its biological applications. Furthermore, the integration of data science and informatics into healthcare necessitates professionals capable of managing and interpreting vast datasets for improved patient care and medical research. The growing aging population, coupled with a rising prevalence of chronic diseases, further intensifies the demand for such skilled individuals. The market is segmented by subject areas including biomedical engineering, health informatics, clinical engineering, and robotics in healthcare; and by course levels, encompassing undergraduate, graduate, and certificate programs. Major players are established universities globally, each with its unique strengths and competitive strategies, focusing on program innovation, industry partnerships, and attracting top faculty. Geographic distribution reveals strong market presence in North America and Europe, owing to established research infrastructure and well-funded educational institutions. However, the APAC region, particularly India and China, shows significant growth potential driven by rapid economic development and increased investment in healthcare infrastructure and education. The market's future growth hinges on sustained investment in research and development, industry-academia collaborations, and government initiatives promoting STEM education. Challenges include the high cost of specialized equipment and training, along with the need for standardized curriculum and accreditation across different regions and institutions. Ultimately, the market's trajectory reflects a critical need for a multidisciplinary approach to address evolving healthcare challenges, presenting substantial opportunities for educational institutions and technology providers alike.