Daniel A. Hashimoto

7.0k total citations · 1 hit paper
87 papers, 3.4k citations indexed

About

Daniel A. Hashimoto is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Health Informatics. According to data from OpenAlex, Daniel A. Hashimoto has authored 87 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Surgery, 26 papers in Cardiology and Cardiovascular Medicine and 19 papers in Health Informatics. Recurrent topics in Daniel A. Hashimoto's work include Surgical Simulation and Training (52 papers), Cardiac, Anesthesia and Surgical Outcomes (26 papers) and Artificial Intelligence in Healthcare and Education (19 papers). Daniel A. Hashimoto is often cited by papers focused on Surgical Simulation and Training (52 papers), Cardiac, Anesthesia and Surgical Outcomes (26 papers) and Artificial Intelligence in Healthcare and Education (19 papers). Daniel A. Hashimoto collaborates with scholars based in United States, Canada and United Kingdom. Daniel A. Hashimoto's co-authors include Ozanan R. Meireles, Guy Rosman, Daniela Rus, Elan R. Witkowski, Thomas M. Ward, Lei Gao, Allison Navarrete-Welton, Keith D. Lillemoe, Amin Madani and Roy Phitayakorn and has published in prestigious journals such as New England Journal of Medicine, SHILAP Revista de lepidopterología and Nature Biotechnology.

In The Last Decade

Daniel A. Hashimoto

80 papers receiving 3.3k 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.

Artificial Intelligence in Surgery: Promises and Perils

2018 746 citations Daniel A. Hashimoto, Guy Rosman et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel A. Hashimoto United States	28	1.8k	888	834	613	533	87	3.4k
Ozanan R. Meireles United States	19	1.2k 0.7×	649 0.7×	505 0.6×	410 0.7×	357 0.7×	45	2.1k
Andrew J. Hung United States	33	2.3k 1.3×	458 0.5×	1.4k 1.7×	665 1.1×	455 0.9×	124	3.8k
Myura Nagendran United Kingdom	23	1.1k 0.6×	353 0.4×	374 0.4×	442 0.7×	367 0.7×	62	2.5k
Aditya V. Karhade United States	35	1.9k 1.1×	665 0.7×	886 1.1×	449 0.7×	351 0.7×	115	3.6k
Samuel K. Cho United States	53	7.6k 4.1×	481 0.5×	1.1k 1.4×	721 1.2×	366 0.7×	366	10.3k
Mahiben Maruthappu United Kingdom	25	578 0.3×	455 0.5×	192 0.2×	511 0.8×	487 0.9×	94	3.1k
Alan Karthikesalingam United Kingdom	43	2.2k 1.2×	871 1.0×	440 0.5×	2.1k 3.4×	1.2k 2.2×	137	6.9k
Elena Bignami Italy	35	1.3k 0.7×	739 0.8×	359 0.4×	1.5k 2.5×	583 1.1×	180	4.4k
Paul H. Yi United States	30	1.3k 0.7×	821 0.9×	329 0.4×	165 0.3×	928 1.7×	148	3.1k
Felix Nickel Germany	37	2.5k 1.4×	102 0.1×	991 1.2×	308 0.5×	258 0.5×	211	3.7k

Countries citing papers authored by Daniel A. Hashimoto

Since Specialization

Citations

This map shows the geographic impact of Daniel A. Hashimoto'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 Daniel A. Hashimoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel A. Hashimoto more than expected).

Fields of papers citing papers by Daniel A. Hashimoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel A. Hashimoto. 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 Daniel A. Hashimoto. The network helps show where Daniel A. Hashimoto may publish in the future.

Co-authorship network of co-authors of Daniel A. Hashimoto

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel A. Hashimoto. A scholar is included among the top collaborators of Daniel A. Hashimoto 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 Daniel A. Hashimoto. Daniel A. Hashimoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Collins, Toby, Daniel A. Hashimoto, Silvana Perretta, et al.. (2025). Surgeons’ awareness, expectations, and involvement with artificial intelligence: a survey pre and post the GPT era. European Journal of Surgical Oncology. 51(12). 110525–110525.

Singh, Vivek, et al.. (2025). Artificial intelligence in surgery: what is needed for ongoing innovation. Surgery (Oxford). 43(3). 129–134.

Masino, Caterina, Adnan Alseidi, Daniel A. Hashimoto, et al.. (2024). LapBot-Safe Chole: validation of an artificial intelligence-powered mobile game app to teach safe cholecystectomy. Surgical Endoscopy. 38(9). 5274–5284. 3 indexed citations

Madani, Amin, Yao Liu, Aurora D. Pryor, et al.. (2024). SAGES surgical data science task force: enhancing surgical innovation, education and quality improvement through data science. Surgical Endoscopy. 38(7). 3489–3493. 2 indexed citations

Mascagni, Pietro, Deepak Alapatt, Maria S. Altieri, et al.. (2022). Computer vision in surgery: from potential to clinical value. npj Digital Medicine. 5(1). 163–163. 102 indexed citations

Chidambaram, Swathikan, Viknesh Sounderajah, Daniel A. Hashimoto, et al.. (2022). Using Artificial Intelligence-Enhanced Sensing and Wearable Technology in Sports Medicine and Performance Optimisation. Sensors. 22(18). 6920–6920. 58 indexed citations

Ward, Thomas M., Pietro Mascagni, Amin Madani, et al.. (2021). Surgical data science and artificial intelligence for surgical education. Journal of Surgical Oncology. 124(2). 221–230. 54 indexed citations

Loftus, Tyler J., Alexander P. J. Vlaar, Andrew J. Hung, et al.. (2021). Executive summary of the artificial intelligence in surgery series. Surgery. 171(5). 1435–1439. 13 indexed citations

Seastedt, Kenneth P., Dana Moukheiber, Ammara A. Watkins, et al.. (2021). A scoping review of artificial intelligence applications in thoracic surgery. European Journal of Cardio-Thoracic Surgery. 61(2). 239–248. 13 indexed citations

10.

Wong, Daniel J., David Miranda-Nieves, Prathima Nandivada, et al.. (2021). The Surgical Program in Innovation (SPIN): A Design and Prototyping Curriculum for Surgical Trainees. Academic Medicine. 96(9). 1306–1310. 6 indexed citations

11.

Namazi, Babak, Amin Madani, Daniel A. Hashimoto, et al.. (2020). AI for Automated Detection of the Establishment of Critical View of Safety in Laparoscopic Cholecystectomy Videos. Journal of the American College of Surgeons. 231(4). e48–e48. 4 indexed citations

12.

Altieri, Maria S., Daniel A. Hashimoto, Babak Namazi, et al.. (2020). Using Artificial Intelligence to Identify Surgical Anatomy, Safe Zones of DISSection, and Dangerous Zones of DISSection during Laparoscopic Cholecystectomy. Journal of the American College of Surgeons. 231(4). e21–e22. 3 indexed citations

13.

Bababekov, Yanik J., Sahael M. Stapleton, Daniel A. Hashimoto, et al.. (2020). Open innovation facilitates department-wide engagement in quality improvement: experience from the Massachusetts General Hospital. Surgical Endoscopy. 35(10). 5441–5449. 3 indexed citations

14.

Hashimoto, Daniel A., Elan R. Witkowski, Lei Gao, Ozanan R. Meireles, & Guy Rosman. (2019). Artificial Intelligence in Anesthesiology. Anesthesiology. 132(2). 379–394. 290 indexed citations

15.

Mehtsun, Winta T., Daniel A. Hashimoto, & Cristina R. Ferrone. (2019). Status of 5-Year Survivors of the Whipple Procedure for Pancreatic Adenocarcinoma. Advances in Surgery. 53. 253–269. 2 indexed citations

16.

Lindeman, Brenessa, Emil Petrusa, Sophia K. McKinley, et al.. (2017). Association of Burnout With Emotional Intelligence and Personality in Surgical Residents: Can We Predict Who Is Most at Risk?. Journal of surgical education. 74(6). e22–e30. 99 indexed citations

17.

Lindeman, Brenessa, Daniel A. Hashimoto, Yanik J. Bababekov, et al.. (2017). Fifteen years of adrenalectomies: impact of specialty training and operative volume. Surgery. 163(1). 150–156. 41 indexed citations

18.

Hashimoto, Daniel A., Pramudith Sirimanna, Ernest Gomez, et al.. (2014). Deliberate practice enhances quality of laparoscopic surgical performance in a randomized controlled trial: from arrested development to expert performance. Surgical Endoscopy. 29(11). 3154–3162. 64 indexed citations

19.

Yang, Rachel, Daniel A. Hashimoto, Jarrod D. Predina, et al.. (2013). The Virtual-Patient Pilot: Testing a New Tool for Undergraduate Surgical Education and Assessment. Journal of surgical education. 70(3). 394–401. 16 indexed citations

20.

Hashimoto, Daniel A., Ernest Gomez, Enrico Danzer, et al.. (2012). Intraoperative Resident Education for Robotic Laparoscopic Gastric Banding Surgery: A Pilot Study on the Safety of Stepwise Education. Journal of the American College of Surgeons. 214(6). 990–996. 13 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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