Akhil Chawla

3.8k total citations · 2 hit papers
44 papers, 2.5k citations indexed

About

Akhil Chawla is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Akhil Chawla has authored 44 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Oncology, 17 papers in Pulmonary and Respiratory Medicine and 16 papers in Cancer Research. Recurrent topics in Akhil Chawla's work include Pancreatic and Hepatic Oncology Research (22 papers), Cancer Genomics and Diagnostics (15 papers) and Renal cell carcinoma treatment (8 papers). Akhil Chawla is often cited by papers focused on Pancreatic and Hepatic Oncology Research (22 papers), Cancer Genomics and Diagnostics (15 papers) and Renal cell carcinoma treatment (8 papers). Akhil Chawla collaborates with scholars based in United States, Italy and Canada. Akhil Chawla's co-authors include Eileen M. O’Reilly, Wungki Park, Elizabeth A. Mittendorf, Gheath Alatrash, Anne V. Philips, Yun Wu, Jeffrey J. Molldrem, Jennifer K. Litton, Funda Meric‐Bernstam and Ying Wang and has published in prestigious journals such as JAMA, Journal of Clinical Oncology and Cancer Research.

In The Last Decade

Akhil Chawla

41 papers receiving 2.5k citations

Hit Papers

PD-L1 Expression in Triple-Negative Breast Cancer 2014 2026 2018 2022 2014 2021 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akhil Chawla United States 13 1.9k 638 614 570 558 44 2.5k
Jean‐Sébastien Frenel France 26 1.4k 0.7× 708 1.1× 801 1.3× 809 1.4× 350 0.6× 188 2.7k
Yuping Sun China 27 1.3k 0.7× 413 0.6× 818 1.3× 502 0.9× 831 1.5× 87 2.4k
Dawei Chen China 24 1.5k 0.8× 323 0.5× 508 0.8× 933 1.6× 554 1.0× 91 2.4k
Jifang Gong China 29 1.7k 0.9× 603 0.9× 785 1.3× 928 1.6× 381 0.7× 147 2.9k
Wenchuan Wu China 23 1.5k 0.8× 651 1.0× 620 1.0× 444 0.8× 377 0.7× 73 2.1k
Wade T. Iams United States 21 1.4k 0.7× 514 0.8× 806 1.3× 718 1.3× 459 0.8× 95 2.2k
Αthanasios Kotsakis Greece 35 2.5k 1.4× 910 1.4× 1.0k 1.7× 1.3k 2.2× 717 1.3× 166 3.6k
Jonathan D. Mizrahi United States 8 1.3k 0.7× 560 0.9× 689 1.1× 375 0.7× 177 0.3× 16 1.9k
Ana C. Garrido-Castro United States 12 1.4k 0.8× 474 0.7× 649 1.1× 502 0.9× 287 0.5× 54 2.2k
Won Jin Ho United States 18 1.3k 0.7× 438 0.7× 612 1.0× 340 0.6× 629 1.1× 59 2.1k

Countries citing papers authored by Akhil Chawla

Since Specialization
Citations

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

Fields of papers citing papers by Akhil Chawla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akhil Chawla. 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 Akhil Chawla. The network helps show where Akhil Chawla may publish in the future.

Co-authorship network of co-authors of Akhil Chawla

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

All Works

20 of 20 papers shown
1.
Vitello, Dominic, et al.. (2024). Surgical Palliation for Advanced Pancreas Cancer. Surgical Clinics of North America. 104(5). 1121–1135.
2.
Chawla, Akhil, et al.. (2024). Liquid-liquid phase separation-related features of PYGB/ACTR3/CCNA2/ITGB1/ATP8A1/RAP1GAP2 predict the prognosis of pancreatic cancer. Journal of Gastrointestinal Oncology. 15(4). 1723–1745.
3.
Jacobs, Ryan C, et al.. (2024). Utilization and survival outcomes of neoadjuvant chemotherapy for early‐stage gastric cancer. Journal of Surgical Oncology. 130(2). 249–256. 1 indexed citations
4.
Gerratana, Lorenzo, Andrew A. Davis, Paolo D’Amico, et al.. (2024). Early Evaluation of Risk Stratification and Clinical Outcomes for Patients with Advanced Breast Cancer through Combined Monitoring of Baseline Circulating Tumor Cells and DNA. Clinical Cancer Research. 30(16). 3470–3480. 2 indexed citations
5.
Bentrem, David J., et al.. (2024). Omission of Chemoradiation in Locally Advanced Rectal Adenocarcinoma: Evaluation of PROSPECT in a National Database. Journal of Surgical Oncology. 130(8). 1662–1673. 1 indexed citations
6.
Vitello, Dominic, Dhavan V. Shah, M.C. Cox, et al.. (2024). Mutant KRAS in Circulating Tumor DNA as a Biomarker in Localized Pancreatic Cancer in Patients Treated with Neoadjuvant Chemotherapy. Annals of Surgery. 6 indexed citations
7.
Cox, M.C., Sohail S. Chaudhry, Qiang Zhang, et al.. (2024). Prospective Evaluation of Circulating Tumor DNA Using Next-generation Sequencing as a Biomarker During Neoadjuvant Chemotherapy in Localized Pancreatic Cancer. Annals of Surgery. 281(6). 997–1005. 9 indexed citations
8.
Chawla, Akhil, et al.. (2023). The differential effect of neoadjuvant chemotherapy and chemoradiation on nodal downstaging in pancreatic adenocarcinoma. Pancreatology. 23(7). 805–810. 2 indexed citations
9.
Chawla, Akhil, et al.. (2023). Weight loss during neoadjuvant chemotherapy impacts perioperative outcomes in patients undergoing surgery for pancreatic cancer. Pancreatology. 23(8). 1020–1027. 4 indexed citations
10.
Vitello, Dominic, et al.. (2023). Comparison of perioperative and histopathologic outcomes among neoadjuvant treatment strategies for locoregional gastric cancer. Journal of Surgical Oncology. 129(3). 481–488. 2 indexed citations
11.
Schlick, Cary Jo R., et al.. (2022). Utility of circulating tumor DNA for predicting prognosis in the management of resectable pancreatic cancer. Journal of Cancer Metastasis and Treatment. 8. 29–29.
12.
Chawla, Akhil, et al.. (2022). Measuring response to neoadjuvant therapy using biomarkers in pancreatic cancer: a narrative review. Chinese Clinical Oncology. 11(4). 30–30. 5 indexed citations
13.
Chawla, Akhil, et al.. (2021). The role of oncologic resection and enucleation for small pancreatic neuroendocrine tumors. HPB. 23(10). 1533–1540. 7 indexed citations
15.
Chawla, Akhil, Jennifer Y. Wo, Carlos Fernández-del Castillo, et al.. (2020). Clinical staging in pancreatic adenocarcinoma underestimates extent of disease. Pancreatology. 20(4). 691–697. 11 indexed citations
16.
Chawla, Akhil & Cristina R. Ferrone. (2019). Neoadjuvant Therapy for Resectable Pancreatic Cancer: An Evolving Paradigm Shift. Frontiers in Oncology. 9. 1085–1085. 42 indexed citations
17.
McKinley, Sophia K., Akhil Chawla, & Cristina R. Ferrone. (2019). Inoperable Biliary Tract and Primary Liver Tumors. Surgical Oncology Clinics of North America. 28(4). 745–762. 3 indexed citations
18.
Chawla, Akhil, Michael H. Rosenthal, & Thomas E. Clancy. (2018). Implications of the replaced right hepatic artery originating from the gastroduodenal artery in the setting of a pancreatic head mass. Clinical Imaging. 52. 189–192. 2 indexed citations
19.
Mittendorf, Elizabeth A., Anne V. Philips, Funda Meric‐Bernstam, et al.. (2014). PD-L1 Expression in Triple-Negative Breast Cancer. Cancer Immunology Research. 2(4). 361–370. 1065 indexed citations breakdown →
20.
Chawla, Akhil, Kelly K. Hunt, & Elizabeth A. Mittendorf. (2012). Surgical Considerations in Patients Receiving Neoadjuvant Systemic Therapy. Future Oncology. 8(3). 239–250. 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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