Amol Takalkar

1.3k total citations
45 papers, 888 citations indexed

About

Amol Takalkar is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Amol Takalkar has authored 45 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Pulmonary and Respiratory Medicine and 13 papers in Oncology. Recurrent topics in Amol Takalkar's work include Medical Imaging Techniques and Applications (14 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Cancer Diagnosis and Treatment (6 papers). Amol Takalkar is often cited by papers focused on Medical Imaging Techniques and Applications (14 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Cancer Diagnosis and Treatment (6 papers). Amol Takalkar collaborates with scholars based in United States, United Kingdom and Brazil. Amol Takalkar's co-authors include David L. Lilien, Abass Alavi, Hongming Zhuang, Klaus Ley, Alexander L. Klibanov, Jonathan R. Lindner, Joshua J. Rychak, Jian Q. Yu, Alok R. Khandelwal and Yan Xiu and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Amol Takalkar

41 papers receiving 869 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Amol Takalkar United States 14 330 272 228 178 168 45 888
Sandra Baleato‐González Spain 16 355 1.1× 168 0.6× 152 0.7× 132 0.7× 136 0.8× 56 819
Pierpaolo Palumbo Italy 20 409 1.2× 274 1.0× 294 1.3× 225 1.3× 160 1.0× 87 1.1k
Sanaz Javadi United States 21 451 1.4× 235 0.9× 386 1.7× 271 1.5× 266 1.6× 70 1.3k
Gustavo Mercier United States 20 723 2.2× 462 1.7× 339 1.5× 240 1.3× 96 0.6× 42 1.4k
Archi Agrawal India 15 318 1.0× 341 1.3× 231 1.0× 237 1.3× 42 0.3× 165 913
Massimo Castellani Italy 18 296 0.9× 266 1.0× 225 1.0× 141 0.8× 50 0.3× 77 843
Gonca Bural United States 16 509 1.5× 396 1.5× 153 0.7× 126 0.7× 53 0.3× 40 951
Shikha Goyal India 18 219 0.7× 336 1.2× 186 0.8× 151 0.8× 63 0.4× 114 802
Chandana Lall United States 18 297 0.9× 319 1.2× 475 2.1× 292 1.6× 87 0.5× 75 1.1k
Harmandeep Singh India 21 482 1.5× 559 2.1× 294 1.3× 251 1.4× 75 0.4× 147 1.2k

Countries citing papers authored by Amol Takalkar

Since Specialization
Citations

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

Fields of papers citing papers by Amol Takalkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amol Takalkar

This figure shows the co-authorship network connecting the top 25 collaborators of Amol Takalkar. A scholar is included among the top collaborators of Amol Takalkar 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 Amol Takalkar. Amol Takalkar 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.
Iagaru, Andrei, Amol Takalkar, Geoff S. Higgins, et al.. (2023). 89Zr-DFO-girentuximab for PET imaging of solid tumors likely to express high levels of carbonic anhydrase IX.. Journal of Clinical Oncology. 41(6_suppl). TPS738–TPS738. 1 indexed citations
2.
Takalkar, Amol & Miguel Hernandez Pampaloni. (2020). Pediatric Cardiac PET/CT Imaging. PET Clinics. 15(3). 371–380. 4 indexed citations
3.
Takalkar, Amol, et al.. (2018). Bone marrow metastases in salivary duct carcinoma of the parotid gland. BMJ Case Reports. 11(1). bcr–2018. 3 indexed citations
4.
Savir-Baruch, Bital, Kevin Banks, Jonathan McConathy, et al.. (2018). ACR–ACNM Practice Parameter for the Performance of Fluorine-18 Fluciclovine-PET/CT for Recurrent Prostate Cancer. Clinical Nuclear Medicine. 43(12). 909–917. 35 indexed citations
5.
Sommerhalder, David, Amol Takalkar, Rodney E. Shackelford, & Prakash Peddi. (2017). Spontaneous tumor lysis syndrome in colon cancer: a case report and literature review. Clinical Case Reports. 5(12). 2121–2126. 22 indexed citations
6.
Takalkar, Amol, et al.. (2017). Follicular dendritic sarcoma masquerading as fibrosing mediastinitis. BMJ Case Reports. 2017. bcr–2016. 8 indexed citations
7.
Caldito, Gloria, et al.. (2017). FDG PET Imaging of Extremities in Rheumatoid Arthritis.. PubMed. 168(5). 156–161. 5 indexed citations
8.
9.
Munker, Reinhold, et al.. (2015). Current role of FDG-PET in Bone and Soft tissue tumors. 1(1). 29–36.
10.
Carbo, Alberto I., et al.. (2014). Acquired Constricting and Restricting Lesions of the Descending Duodenum. Radiographics. 34(5). 1196–1217. 7 indexed citations
11.
Takalkar, Amol, et al.. (2013). Abstract 4697: SUV max of primary lung tumor on FDGPET/CT scan at baseline as a potential prognostic factor in stage IV NSCLC: a retrospective review.. Cancer Research. 73(8_Supplement). 4697–4697. 4 indexed citations
12.
Khandelwal, Alok R., et al.. (2012). Skeletal Muscle Metastases on FDG PET/CT Imaging. Clinical Nuclear Medicine. 37(6). 575–579. 48 indexed citations
13.
Khandelwal, Alok R., et al.. (2011). Incidental Detection of Unsuspected Pulmonary Embolism on Oncologic FDG PET/CT Imaging. Clinical Nuclear Medicine. 36(8). 720–722. 4 indexed citations
14.
Dhawan, Manish, et al.. (2011). FDG PET/CT Imaging Suggests Lymphoma Involving Prostate May Be More Resistant to Treatment. Clinical Nuclear Medicine. 36(3). 255–257. 3 indexed citations
15.
Patterson, James C., David L. Lilien, Amol Takalkar, Roger E. Kelley, & Alireza Minagar. (2008). Potential Value of Quantitative Analysis of Cerebral PET in Early Cognitive Decline. American Journal of Alzheimer s Disease & Other Dementias®. 23(6). 586–592. 6 indexed citations
16.
Takalkar, Amol, Ghassan El‐Haddad, David L. Lilien, & James C. Patterson. (2008). Simultaneous Demonstration of Metabolic Lesions Consistent With Alzheimer Disease and Brain Metastases on FDG-PET Imaging. Clinical Nuclear Medicine. 33(6). 438–440. 1 indexed citations
17.
Sangster, Guillermo, et al.. (2007). Accurate Grading of 3 Synchronous Liposarcomas Assessed by PET-CT in a Single Patient. Clinical Nuclear Medicine. 32(12). 937–939. 8 indexed citations
18.
Hernandez‐Pampaloni, Miguel, Amol Takalkar, Jian Q. Yu, Hongming Zhuang, & Abass Alavi. (2006). F-18 FDG-PET imaging and correlation with CT in staging and follow-up of pediatric lymphomas. Pediatric Radiology. 36(6). 524–531. 60 indexed citations
19.
Takalkar, Amol, Alexander L. Klibanov, Joshua J. Rychak, Jonathan R. Lindner, & Klaus Ley. (2004). Binding and detachment dynamics of microbubbles targeted to P-selectin under controlled shear flow. Journal of Controlled Release. 96(3). 473–482. 183 indexed citations
20.
Takalkar, Amol, Jian Yu, Rakesh Kumar, et al.. (2004). Diffuse Bone Marrow Accumulation of FDG in a Patient With Chronic Myeloid Leukemia Mimics Hematopoietic Cytokine-Mediated FDG Uptake on Positron Emission Tomography. Clinical Nuclear Medicine. 29(10). 637–639. 46 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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