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Artificial Intelligence in Healthcare: 2023 Year in Review

Awasthi, R.; Mishra, S.; Grasfield, R.; Maslinski, J.; Mahapatra, D.; Cywinski, J. B.; Khanna, A. K.; Maheshwari, K.; Dave, C.; Khare, A.; Papay, F. A.; Mathur, P.

2024-02-29 health informatics Community evaluation
10.1101/2024.02.28.24303482 medRxiv
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BackgroundThe infodemic we are experiencing with AI related publications in healthcare is unparalleled. The excitement and fear surrounding the adoption of rapidly evolving AI in healthcare applications pose a real challenge. Collaborative learning from published research is one of the best ways to understand the associated opportunities and challenges in the field. To gain a deep understanding of recent developments in this field, we have conducted a quantitative and qualitative review of AI in healthcare research articles published in 2023. MethodsWe performed a PubMed search using the terms, "machine learning" or "artificial intelligence" and "2023", restricted to English language and human subject research as of December 31, 2023 on January 1, 2024. Utilizing a Deep Learning-based approach, we assessed the maturity of publications. Following this, we manually annotated the healthcare specialty, data utilized, and models employed for the identified mature articles. Subsequently, empirical data analysis was performed to elucidate trends and statistics.Similarly, we performed a search for Large Language Model(LLM) based publications for the year 2023. ResultsOur PubMed search yielded 23,306 articles, of which 1,612 were classified as mature. Following exclusions, 1,226 articles were selected for final analysis. Among these, the highest number of articles originated from the Imaging specialty (483), followed by Gastroenterology (86), and Ophthalmology (78). Analysis of data types revealed that image data was predominant, utilized in 75.2% of publications, followed by tabular data (12.9%) and text data (11.6%). Deep Learning models were extensively employed, constituting 59.8% of the models used. For the LLM related publications,after exclusions, 584 publications were finally classified into the 26 different healthcare specialties and used for further analysis. The utilization of Large Language Models (LLMs), is highest in general healthcare specialties, at 20.1%, followed by surgery at 8.5%. ConclusionImage based healthcare specialities such as Radiology, Gastroenterology and Cardiology have dominated the landscape of AI in healthcare research for years. In the future, we are likely to see other healthcare specialties including the education and administrative areas of healthcare be driven by the LLMs and possibly multimodal models in the next era of AI in healthcare research and publications.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
BMJ Health & Care Informatics
13 papers in training set
Top 0.1%
14.5%
2
BMC Medical Informatics and Decision Making
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Top 0.2%
12.2%
3
European Radiology
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Top 0.2%
4.8%
4
JMIR Medical Informatics
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4.2%
5
International Journal of Medical Informatics
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Top 0.3%
3.9%
6
Artificial Intelligence in Medicine
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3.5%
7
Frontiers in Medicine
113 papers in training set
Top 2%
3.5%
8
Biology Methods and Protocols
53 papers in training set
Top 0.3%
3.5%
50% of probability mass above
9
BMJ Open
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3.5%
10
Scientific Reports
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11
PLOS Digital Health
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Top 0.8%
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12
Computer Methods and Programs in Biomedicine
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13
PLOS ONE
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Top 46%
2.4%
14
Frontiers in Artificial Intelligence
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Top 0.2%
2.0%
15
Computers in Biology and Medicine
120 papers in training set
Top 2%
2.0%
16
JAMIA Open
37 papers in training set
Top 0.8%
1.8%
17
npj Digital Medicine
97 papers in training set
Top 2%
1.7%
18
Healthcare
16 papers in training set
Top 1.0%
1.3%
19
Frontiers in Public Health
140 papers in training set
Top 6%
1.3%
20
Cureus
67 papers in training set
Top 4%
1.1%
21
Sensors
39 papers in training set
Top 1%
1.1%
22
Journal of the American Medical Informatics Association
61 papers in training set
Top 2%
1.1%
23
Frontiers in Physiology
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1.1%
24
Informatics in Medicine Unlocked
21 papers in training set
Top 0.9%
0.9%
25
JMIR Public Health and Surveillance
45 papers in training set
Top 3%
0.9%
26
Journal of Medical Internet Research
85 papers in training set
Top 5%
0.7%
27
Experimental Neurology
57 papers in training set
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0.7%
28
GigaScience
172 papers in training set
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0.7%