Amin Dada

537 total citations · 1 hit paper
9 papers, 187 citations indexed

About

Amin Dada is a scholar working on Artificial Intelligence, Health Informatics and Health Information Management. According to data from OpenAlex, Amin Dada has authored 9 papers receiving a total of 187 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Health Informatics and 2 papers in Health Information Management. Recurrent topics in Amin Dada's work include Artificial Intelligence in Healthcare and Education (5 papers), Machine Learning in Healthcare (4 papers) and Topic Modeling (4 papers). Amin Dada is often cited by papers focused on Artificial Intelligence in Healthcare and Education (5 papers), Machine Learning in Healthcare (4 papers) and Topic Modeling (4 papers). Amin Dada collaborates with scholars based in Germany, Canada and United States. Amin Dada's co-authors include Jens Kleesiek, Jan Egger, Jianning Li, Behrus Puladi, Felix Nensa, Felix Busch, Daniel Truhn, Keno K. Bressem, Moon Kim and Tianyu Han and has published in prestigious journals such as Journal of the American Medical Informatics Association, European Radiology and Computer Methods and Programs in Biomedicine.

In The Last Decade

Amin Dada

5 papers receiving 184 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

ChatGPT in healthcare: A taxonomy and systematic review

2024 171 citations Jianning Li, Amin Dada et al. Computer Methods and Programs in Biomedicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Amin Dada Germany	4	108	81	43	25	18	9	187
Joshua Au Yeung United Kingdom	7	118 1.1×	92 1.1×	45 1.0×	19 0.8×	20 1.1×	11	224
Ashwin Nayak United States	8	101 0.9×	96 1.2×	37 0.9×	21 0.8×	18 1.0×	9	235
Brenda Y. Miao United States	8	125 1.2×	104 1.3×	72 1.7×	23 0.9×	25 1.4×	14	287
Shan Chen United States	5	88 0.8×	105 1.3×	39 0.9×	34 1.4×	25 1.4×	9	231
Dev Dash United States	6	112 1.0×	73 0.9×	50 1.2×	16 0.6×	14 0.8×	9	209
Shawheen J. Rezaei United States	6	81 0.8×	60 0.7×	39 0.9×	18 0.7×	19 1.1×	26	239
Sophia M. Pressman United States	9	146 1.4×	64 0.8×	51 1.2×	21 0.8×	14 0.8×	18	229
Asad Aali United States	3	109 1.0×	131 1.6×	55 1.3×	15 0.6×	35 1.9×	6	268
Ibraheem Altamimi Saudi Arabia	7	115 1.1×	55 0.7×	47 1.1×	24 1.0×	5 0.3×	14	191
Mayli Mertens Belgium	6	89 0.8×	47 0.6×	26 0.6×	14 0.6×	7 0.4×	12	209

Countries citing papers authored by Amin Dada

Since Specialization

Citations

This map shows the geographic impact of Amin Dada's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Amin Dada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amin Dada more than expected).

Fields of papers citing papers by Amin Dada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amin Dada. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Amin Dada. The network helps show where Amin Dada may publish in the future.

Co-authorship network of co-authors of Amin Dada

This figure shows the co-authorship network connecting the top 25 collaborators of Amin Dada. A scholar is included among the top collaborators of Amin Dada based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Amin Dada. Amin Dada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Dada, Amin, et al.. (2025). MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters. 124–136.

2.

Baldini, Giulia, et al.. (2025). FHIR-Former: enhancing clinical predictions through Fast Healthcare Interoperability Resources and large language models. Journal of the American Medical Informatics Association. 32(12). 1793–1801.

3.

Kleesiek, Jens, et al.. (2025). Towards Conditioning Clinical Text Generation for User Control. 10549–10569. 1 indexed citations

4.

Baldini, Giulia, Daniel Truhn, Gustav Müller‐Franzes, et al.. (2025). An automated information extraction model for unstructured discharge letters using large language models and GPT-4. Healthcare Analytics. 7. 100378–100378. 3 indexed citations

5.

Dada, Amin, et al.. (2025). Implementierung von künstlicher Intelligenz (KI) im Gesundheitswesen: Historische Entwicklung, aktuelle Technologien und Herausforderungen. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz. 68(8). 845–853.

6.

Dada, Amin, Felix Busch, Marcus R. Makowski, et al.. (2025). Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks. Journal of the American Medical Informatics Association. 32(6). 1015–1024. 5 indexed citations

7.

Li, Jianning, Amin Dada, Behrus Puladi, Jens Kleesiek, & Jan Egger. (2024). ChatGPT in healthcare: A taxonomy and systematic review. Computer Methods and Programs in Biomedicine. 245. 108013–108013. 171 indexed citations breakdown →

8.

Dada, Amin, et al.. (2024). IKIM at MEDIQA-M3G 2024: Multilingual Visual Question-Answering for Dermatology through VLM Fine-tuning and LLM Translations. 439–447.

9.

Dada, Amin, Moon Kim, Michael Forsting, et al.. (2023). Information extraction from weakly structured radiological reports with natural language queries. European Radiology. 34(1). 330–337. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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