Hitesh Mistry

2.1k total citations
100 papers, 1.2k citations indexed

About

Hitesh Mistry is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hitesh Mistry has authored 100 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Oncology, 35 papers in Pulmonary and Respiratory Medicine and 22 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hitesh Mistry's work include Lung Cancer Research Studies (12 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Lung Cancer Treatments and Mutations (10 papers). Hitesh Mistry is often cited by papers focused on Lung Cancer Research Studies (12 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Lung Cancer Treatments and Mutations (10 papers). Hitesh Mistry collaborates with scholars based in United Kingdom, United States and France. Hitesh Mistry's co-authors include Corinne Faivre‐Finn, Fiona Blackhall, James P.B. O’Connor, Gareth Price, Andrew McPartlin, Ananya Choudhury, Isabella Fornacon-Wood, Christoph Ackermann, Andrew J. McBain and Mark Davies and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Hitesh Mistry

91 papers receiving 1.2k citations

Peers

Hitesh Mistry
Rong Tian China
Anthony D. Kang United States
Xiaoming Yang China
Akihiro Hayashi Japan
Iris Burkholder Germany
Xiaoyang Li China
Santhanam Sundar United Kingdom
Chao Zhou China
Zhijun Wang China
Pan Liang China
Rong Tian China
Hitesh Mistry
Citations per year, relative to Hitesh Mistry Hitesh Mistry (= 1×) peers Rong Tian

Countries citing papers authored by Hitesh Mistry

Since Specialization
Citations

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

Fields of papers citing papers by Hitesh Mistry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hitesh Mistry

This figure shows the co-authorship network connecting the top 25 collaborators of Hitesh Mistry. A scholar is included among the top collaborators of Hitesh Mistry 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 Hitesh Mistry. Hitesh Mistry 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.
Mistry, Hitesh, David Hodson, Michael M. Schmidt, et al.. (2025). A Pharmacokinetic and Pharmacodynamic Model of an IL-12 Anchored-Drug Conjugate for the Treatment of Solid Tumors. Molecular Cancer Therapeutics. 24(7). 1054–1062.
2.
Choules, Mary, Frances A. Brightman, Nobuaki Amino, et al.. (2025). A Multiple‐Model‐Informed Drug‐Development Approach for Optimal Regimen Selection of an Oncolytic Virus in Combination With Pembrolizumab. CPT Pharmacometrics & Systems Pharmacology. 14(3). 572–582. 3 indexed citations
3.
4.
Huang, Zhonghui, Paolo Denti, Hitesh Mistry, & Frank Kloprogge. (2024). Machine Learning and Artificial Intelligence in PK‐PD Modeling: Fad, Friend, or Foe?. Clinical Pharmacology & Therapeutics. 115(4). 652–654. 12 indexed citations
5.
Hodson, David, Hitesh Mistry, James Yates, et al.. (2024). Hierarchical cluster analysis and nonlinear mixed-effects modelling for candidate biomarker detection in preclinical models of cancer.. European Journal of Pharmaceutical Sciences. 197. 106774–106774. 3 indexed citations
6.
Walls, Gerard, Hitesh Mistry, Fabrice Barlési, et al.. (2024). Long-Term Outcomes After Concurrent Once- or Twice-Daily Chemoradiation in Limited-Stage Small Cell Lung Cancer: A Brief Report From the CONVERT Trial. International Journal of Radiation Oncology*Biology*Physics. 119(5). 1386–1390. 6 indexed citations
7.
Huber, Heinrich J. & Hitesh Mistry. (2023). Explaining in-vitro to in-vivo efficacy correlations in oncology pre-clinical development via a semi-mechanistic mathematical model. Journal of Pharmacokinetics and Pharmacodynamics. 51(2). 169–185. 5 indexed citations
8.
Bibby, B., Lingjian Yang, Brian R. Lane, et al.. (2023). Technical development and validation of a clinically applicable microenvironment classifier as a biomarker of tumour hypoxia for soft tissue sarcoma. British Journal of Cancer. 128(12). 2307–2317. 4 indexed citations
9.
Tindall, Marcus J., L. Cucurull-Sanchez, Hitesh Mistry, & James Yates. (2023). Quantitative Systems Pharmacology and Machine Learning: A Match Made in Heaven or Hell?. Journal of Pharmacology and Experimental Therapeutics. 387(1). 92–99. 6 indexed citations
10.
Mistry, Hitesh. (2023). Radiosensitivity Index is Not Fit to be Used for Dose Adjustments: A Pan-Cancer Analysis. Clinical Oncology. 35(9). 565–570. 4 indexed citations
11.
Gajjar, Parmesh, et al.. (2022). Determining bioequivalence possibilities of long acting injectables through population PK modelling. European Journal of Pharmaceutical Sciences. 179. 106296–106296. 9 indexed citations
12.
Price, James, Hitesh Mistry, Guy Betts, et al.. (2022). Pretreatment Lymphocyte Count Predicts Benefit From Concurrent Chemotherapy With Radiotherapy in Oropharyngeal Cancer. Journal of Clinical Oncology. 40(20). 2203–2212. 16 indexed citations
13.
Fornacon-Wood, Isabella, et al.. (2022). Bayesian methods provide a practical real-world evidence framework for evaluating the impact of changes in radiotherapy. Radiotherapy and Oncology. 176. 53–58. 1 indexed citations
14.
Gomes, Fábio, Corinne Faivre‐Finn, Hitesh Mistry, et al.. (2021). Safety of G-CSF with concurrent chemo-radiotherapy in limited-stage small cell lung cancer - Secondary analysis of the randomised phase 3 CONVERT trial. Lung Cancer. 153. 165–170. 8 indexed citations
15.
Aversa, Caterina, Arighno Das, Deborah Enting, et al.. (2020). 765P Predicting survival in urothelial cancer patients after immunotherapy using real-world data. Annals of Oncology. 31. S590–S590. 3 indexed citations
16.
Salem, Ahmed, Ross A. Little, Ayşe Latif, et al.. (2019). Oxygen-enhanced MRI Is Feasible, Repeatable, and Detects Radiotherapy-induced Change in Hypoxia in Xenograft Models and in Patients with Non–small Cell Lung Cancer. Clinical Cancer Research. 25(13). 3818–3829. 61 indexed citations
17.
McWilliam, Alan, Jason Kennedy, Hitesh Mistry, et al.. (2019). Post-treatment lymphocytopaenia, integral body dose and overall survival in lung cancer patients treated with radical radiotherapy. Radiotherapy and Oncology. 135. 115–119. 35 indexed citations
18.
19.
Beasley, William, L. Dixon, Kate Garcez, et al.. (2018). Use of a novel atlas for muscles of mastication to reduce inter observer variability in head and neck radiotherapy contouring. Radiotherapy and Oncology. 130. 56–61. 15 indexed citations
20.
Mistry, Hitesh, et al.. (2016). Predicting survival of pancreatic cancer patients treated with gemcitabine using longitudinal tumour size data. Cancer Chemotherapy and Pharmacology. 77(5). 927–938. 8 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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