Pallavi Tiwari

3.7k total citations · 1 hit paper
71 papers, 2.2k citations indexed

About

Pallavi Tiwari is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Pallavi Tiwari has authored 71 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Radiology, Nuclear Medicine and Imaging, 28 papers in Genetics and 14 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Pallavi Tiwari's work include Radiomics and Machine Learning in Medical Imaging (48 papers), Glioma Diagnosis and Treatment (28 papers) and AI in cancer detection (14 papers). Pallavi Tiwari is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (48 papers), Glioma Diagnosis and Treatment (28 papers) and AI in cancer detection (14 papers). Pallavi Tiwari collaborates with scholars based in United States, Netherlands and India. Pallavi Tiwari's co-authors include Anant Madabhushi, Prateek Prasanna, Nathaniel Braman, Donna Plecha, Christina Dubchuk, Maryam Etesami, Hannah Gilmore, Niha Beig, Kaustav Bera and Sasan Partovi and has published in prestigious journals such as PLoS ONE, Scientific Reports and Radiology.

In The Last Decade

Pallavi Tiwari

64 papers receiving 2.2k citations

Hit Papers

Intratumoral and peritumo... 2017 2026 2020 2023 2017 100 200 300 400
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.

  1. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI
    2017 479 citations Nathaniel Braman, Maryam Etesami et al. Breast Cancer Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pallavi Tiwari United States 20 1.8k 661 537 416 409 71 2.2k
Martin Vallières Canada 22 3.0k 1.7× 1.1k 1.6× 390 0.7× 567 1.4× 816 2.0× 48 3.3k
Mu Zhou United States 20 2.5k 1.4× 1.4k 2.2× 303 0.6× 842 2.0× 365 0.9× 40 3.1k
Sebastian Echegaray United States 16 1.3k 0.7× 542 0.8× 257 0.5× 260 0.6× 236 0.6× 22 1.5k
Niha Beig United States 18 1.5k 0.8× 672 1.0× 354 0.7× 282 0.7× 339 0.8× 31 1.7k
Yali Zang China 20 1.6k 0.9× 926 1.4× 154 0.3× 411 1.0× 298 0.7× 42 2.1k
R. Jena United Kingdom 30 1.2k 0.7× 613 0.9× 648 1.2× 116 0.3× 203 0.5× 109 2.6k
Yuhua Gu United States 9 2.2k 1.2× 875 1.3× 153 0.3× 489 1.2× 671 1.6× 20 2.5k
Alireza Mehrtash United States 16 1.2k 0.7× 443 0.7× 85 0.2× 482 1.2× 328 0.8× 32 1.8k
Jeon‐Hor Chen Taiwan 34 2.4k 1.4× 655 1.0× 166 0.3× 1.2k 2.8× 328 0.8× 128 3.5k
Sylvain Reuzé France 12 1.7k 1.0× 565 0.9× 139 0.3× 232 0.6× 436 1.1× 18 2.0k

Countries citing papers authored by Pallavi Tiwari

Since Specialization
Citations

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

Fields of papers citing papers by Pallavi Tiwari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pallavi Tiwari

This figure shows the co-authorship network connecting the top 25 collaborators of Pallavi Tiwari. A scholar is included among the top collaborators of Pallavi Tiwari 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 Pallavi Tiwari. Pallavi Tiwari 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.
Buckingham, William R., Erin M. Jonaitis, Rebecca E. Langhough, et al.. (2025). Association of neighborhood disadvantage with cognitive function and cortical disorganization in an unimpaired cohort: An exploratory study. Alzheimer s & Dementia. 21(3). e70095–e70095.
2.
Ozair, Ahmad, Mustafa Khasraw, Graeme F. Woodworth, et al.. (2024). Immune checkpoint inhibitors for glioblastoma: emerging science, clinical advances, and future directions. Journal of Neuro-Oncology. 171(3). 531–547. 9 indexed citations
3.
Li, Chengnan, et al.. (2024). Leveraging radiomics and machine learning to differentiate radiation necrosis from recurrence in patients with brain metastases. Journal of Neuro-Oncology. 168(2). 307–316. 5 indexed citations
4.
5.
Battalapalli, Dheerendranath, Marwa Ismail, Virginia Hill, et al.. (2024). Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. 1–5. 1 indexed citations
6.
Gomez, Felicia, Arpad Danos, Guilherme Del Fiol, et al.. (2024). A New Era of Data-Driven Cancer Research and Care: Opportunities and Challenges. Cancer Discovery. 14(10). 1774–1778.
7.
Bareja, Rohan, Marwa Ismail, Douglas Martin, et al.. (2024). nnU-Net–based Segmentation of Tumor Subcompartments in Pediatric Medulloblastoma Using Multiparametric MRI: A Multi-institutional Study. Radiology Artificial Intelligence. 6(5). e230115–e230115. 4 indexed citations
8.
9.
Verma, Ruchika, Tyler Alban, Mojgan Mokhtari, et al.. (2024). Sexually dimorphic computational histopathological signatures prognostic of overall survival in high-grade gliomas via deep learning. Science Advances. 10(34). eadi0302–eadi0302. 4 indexed citations
10.
Bhatia, Ankush, Anne S. Reiner, Subhiksha Nandakumar, et al.. (2023). Tumor Volume Growth Rates and Doubling Times during Active Surveillance of IDH-mutant Low-Grade Glioma. Clinical Cancer Research. 30(1). 106–115. 13 indexed citations
11.
Verma, Ruchika, Virginia Hill, Volodymyr Statsevych, et al.. (2022). Stable and Discriminatory Radiomic Features from the Tumor and Its Habitat Associated with Progression-Free Survival in Glioblastoma: A Multi-Institutional Study. American Journal of Neuroradiology. 43(8). 1115–1123. 15 indexed citations
12.
Pati, Sarthak, Ruchika Verma, Hamed Akbari, et al.. (2020). Reproducibility analysis of multi‐institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset. Medical Physics. 47(12). 6039–6052. 28 indexed citations
13.
Beig, Niha, Kaustav Bera, Prateek Prasanna, et al.. (2020). Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma. Clinical Cancer Research. 26(8). 1866–1876. 92 indexed citations
14.
15.
Beig, Niha, Mohammadhadi Khorrami, Mehdi Alilou, et al.. (2018). Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas. Radiology. 290(3). 783–792. 238 indexed citations
16.
Ismail, Marwa, Virginia Hill, Volodymyr Statsevych, et al.. (2018). Shape Features of the Lesion Habitat to Differentiate Brain Tumor Progression from Pseudoprogression on Routine Multiparametric MRI: A Multisite Study. American Journal of Neuroradiology. 39(12). 2187–2193. 74 indexed citations
17.
Braman, Nathaniel, Maryam Etesami, Prateek Prasanna, et al.. (2017). Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Research. 19(1). 57–57. 479 indexed citations breakdown →
18.
Madabhushi, Anant, Satish E. Viswanath, George Lee, & Pallavi Tiwari. (2013). Medical Image Informatics for Personalized Medicine. 6(3). 30–33. 1 indexed citations
19.
Tóth, Róbert, Pallavi Tiwari, Mark Rosen, et al.. (2010). A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation. Medical Image Analysis. 15(2). 214–225. 32 indexed citations
20.
Tiwari, Pallavi, Mark Rosen, & Anant Madabhushi. (2008). Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy. Lecture notes in computer science. 11(Pt 2). 330–338. 14 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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