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Topic · Health Informatics

Artificial Intelligence in Healthcare and Education

Artificial Intelligence in Healthcare and Education is a research topic within Health Informatics. Science Explorer counts 42k research works in it since 1954. 9.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the intersection of artificial intelligence and medicine, focusing on applications in healthcare, medical imaging, clinical decision support, and the ethical challenges associated with AI implementation. It delves into topics such as machine learning, big data, precision medicine, and the potential impact of AI on health equity.

  • Artificial Intelligence
  • Machine Learning
  • Healthcare
  • Medical Imaging
  • Clinical Decision Support
  • Ethical Challenges
  • Big Data
  • Precision Medicine
  • Radiology
  • Health Equity
Research works
42k
fractional, since 1954
In the world top 10%
4.1k
per year above
Top-10% rate
9.8%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+543%
the tick is no change
Largest producer
United States
38% of the 10 largest, 2022-now
Artificial Intelligence in Healthcare and Education

This ranks research output and citation impact. It says nothing about the quality of diagnosis, treatment or care.

Which countries lead Artificial Intelligence in Healthcare and Education research?

By volume, the United States and India publish the most (8.7k and 3.4k works in 2022-now).

By volume, 2022-now

  1. 1 United States 8.7k works
  2. 2 India 3.4k works
  3. 3 China 3k works
  4. 4 United Kingdom 1.9k works
  5. 5 Germany 1.3k works
  6. 6 Türkiye 1k works
  7. 7 Canada 927 works
  8. 8 Australia 832 works
  9. 9 Italy 829 works
  10. 10 Indonesia 802 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 38.4%India: 14.9%China: 13.4%United Kingdom: 8.3%6 others listed: 25.1%38%largest
United States8,681 · 38.4%India3,360 · 14.9%China3,021 · 13.4%United Kingdom1,875 · 8.3%6 others listed5,675 · 25.1%

Shares of the rows listed above, not of the whole node.

Which institutions lead Artificial Intelligence in Healthcare and Education research?

By volume in 2022-now, Design Intelligence (United States) publishes the most Artificial Intelligence in Healthcare and Education research, followed by Harvard University and Mayo Clinic.

By volume, 2022-now

  1. 1 Design Intelligence (United States)United States 446 works
  2. 2 Harvard UniversityUnited States 285 works
  3. 3 Mayo ClinicUnited States 184 works
  4. 4 Stanford UniversityUnited States 163 works
  5. 5 University of TorontoCanada 143 works
  6. 6 Johns Hopkins UniversityUnited States 113 works
  7. 7 University College LondonUnited Kingdom 104 works
  8. 8 New York UniversityUnited States 95 works
  9. 9 Yale UniversityUnited States 94 works
  10. 10 University of North Carolina at Chapel HillUnited States 93 works

Who are the leading researchers in Artificial Intelligence in Healthcare and Education?

The most-cited researchers publishing on Artificial Intelligence in Healthcare and Education include David Moher, Douglas G. Altman and Jennifer Tetzlaff.

  1. 1 David Moher Canada 898k citations
  2. 2 Douglas G. Altman United Kingdom 862k citations
  3. 3 Jennifer Tetzlaff Canada 495k citations
  4. 4 Yoshua Bengio Canada 476k citations
  5. 5 Geoffrey E. Hinton Canada 454k citations
  6. 6 Robert John Tibshirani United States 396k citations
  7. 7 Julian P. T. Higgins United Kingdom 390k citations
  8. 8 Zulfiqar Ahmed Bhutta Pakistan 371k citations
  9. 9 John J.V. McMurray United Kingdom 349k citations
  10. 10 Emelia J. Benjamin United States 341k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Artificial Intelligence in Healthcare and Education?

The most cited paper in Artificial Intelligence in Healthcare and Education is "Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead" (Cynthia D Rudin, 2019), with 10,230 citations. Next come "High-performance medicine: the convergence of human and artificial intelligence" (10,125) and "Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI" (10,008).

Most cited papers
#PaperReleasedCitations
1 Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead Cynthia D Rudin · Nature Machine Intelligence Open access 13 May 2019 10,230
2 High-performance medicine: the convergence of human and artificial intelligence Eric J. Topol · Nature Medicine 28 Dec 2018 10,125
3 Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser et al. · Information Fusion Open access 26 Dec 2019 10,008
4 BioBERT: a pre-trained biomedical language representation model for biomedical text mining Jinhyuk Lee, Wonjin Yoon, Sungdong Kim et al. · Bioinformatics Open access 5 Sep 2019 7,445
5 Systematic review of research on artificial intelligence applications in higher education – where are the educators? Olaf Zawacki‐Richter, Victoria I. Marín, Melissa Bond et al. · International Journal of Educational Technology in Higher Education ReviewOpen access 27 Oct 2019 6,707
All 99 most cited papers, with filters and sorting

Where is Artificial Intelligence in Healthcare and Education research done?

The largest centres of Artificial Intelligence in Healthcare and Education research in 2022-now are London (United Kingdom), Beijing (China), Norman (United States) and New York (United States). Among places with at least 20 works in it, it is an unusually large share of all research in Issy-les-Moulineaux and Norman.

Largest cities, 2022-now

  1. 1 LondonUnited Kingdom 585 works
  2. 2 BeijingChina 485 works
  3. 3 NormanUnited States 455 works
  4. 4 New YorkUnited States 452 works
  5. 5 BostonUnited States 295 works
  6. 6 SeoulSouth Korea 279 works
  7. 7 ChennaiIndia 265 works
  8. 8 ShanghaiChina 265 works
  9. 9 TorontoCanada 260 works
  10. 10 SingaporeSingapore 239 works

Where it is the local speciality

  1. Issy-les-MoulineauxFR · 91.4 works104×
  2. NormanUS · 454.9 works41×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Artificial Intelligence in Healthcare and Education than the world average.

See Artificial Intelligence in Healthcare and Education on the map

Where is the best place to study Artificial Intelligence in Healthcare and Education?

Among universities, judged by research, Harvard University, Stanford University and National University of Singapore score highest, combining citation excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 18.78%fractional works in this field (log) →share of work in the world top 10% →Education University…Stanford UniversityNational University …Harvard University
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Citation excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Harvard UniversityUnited States 70.915.8%3.0×285 +217.0%
2Stanford UniversityUnited States 68.419.1%3.7×163 +250.9%
3National University of SingaporeSingapore 63.318.7%2.3×82 +395.7%
4Education University of Hong KongChina 62.732.4%5.1×22 -
5University of Hong KongChina 61.920.6%2.0×55 +763.7%
6University of TorontoCanada 61.513.7%2.4×143 +269.6%
7University of OxfordUnited Kingdom 58.816.2%1.9×80 +124.4%
8University College LondonUnited Kingdom 57.512.9%2.2×104 +331.6%
9Qatar UniversityQatar 57.124.0%2.7×23 +1176.3%
10Johns Hopkins UniversityUnited States 57.014.4%2.4×112 +334.3%

Universities only. The score blends citation excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Artificial Intelligence in Healthcare and Education, country by country

Is Artificial Intelligence in Healthcare and Education research growing?

Output in 2022-2025 was 543% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Artificial Intelligence in Healthcare and Education.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Artificial Intelligence in Healthcare and Education as a percentage of every work published that year, 0.13% in 2024.

still counting0.10%0.20%0.30%Artificial Intelligence in Healthcare and Education0.21% in 202519801990200020102020

Fractional works of Artificial Intelligence in Healthcare and Education over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Artificial Intelligence in Healthcare and Education9.8% in 20252020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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