Peter G. Mikhael

1.6k total citations · 3 hit papers
12 papers, 876 citations indexed

About

Peter G. Mikhael is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Artificial Intelligence. According to data from OpenAlex, Peter G. Mikhael has authored 12 papers receiving a total of 876 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Pulmonary and Respiratory Medicine, 4 papers in Oncology and 4 papers in Artificial Intelligence. Recurrent topics in Peter G. Mikhael's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Lung Cancer Diagnosis and Treatment (4 papers) and AI in cancer detection (4 papers). Peter G. Mikhael is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Lung Cancer Diagnosis and Treatment (4 papers) and AI in cancer detection (4 papers). Peter G. Mikhael collaborates with scholars based in United States, Taiwan and Sweden. Peter G. Mikhael's co-authors include Regina Barzilay, Sydney M. Sanderson, Jason W. Locasale, Ziwei Dai, John P. Richie, Min Lu, Amy Ciccarella, David S. Hsu, Sailendra N. Nichenametla and Ana Calcagnotto and has published in prestigious journals such as Nature, Science and Nature Medicine.

In The Last Decade

Peter G. Mikhael

12 papers receiving 858 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.

Dietary methionine influences therapy in mouse cancer models and alters human metabolism

2019 439 citations Xia Gao, Sydney M. Sanderson et al. Nature profile →
Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography

2023 114 citations Peter G. Mikhael, Jeremy Wohlwend et al. Journal of Clinical Oncology profile →
Protein codes promote selective subcellular compartmentalization

2025 25 citations Henry R. Kilgore, Peter G. Mikhael et al. Science profile →

Peers

Peter G. Mikhael

MB

RNMI

CR

AI

PRM

Tejal Patel United States

Jae Ho Seo United States

Zhi-Ming Shao China

Kaihong Liu United States

Mark E. Bernard United States

Edward Curry United Kingdom

Natalie I. Vokes United States

Mingheng Liao China

Ryan Goosen Switzerland

Carol Geppert Germany

Tejal Patel United States

Peter G. Mikhael

191 ×0.5

MB

69 ×0.3

RNMI

141 ×0.7

CR

58 ×0.3

AI

70 ×0.5

PRM

Citations per year, relative to Peter G. Mikhael Peter G. Mikhael (= 1×) peers Tejal Patel

Countries citing papers authored by Peter G. Mikhael

Since Specialization

Citations

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

Fields of papers citing papers by Peter G. Mikhael

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter G. Mikhael. 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 Peter G. Mikhael. The network helps show where Peter G. Mikhael may publish in the future.

Co-authorship network of co-authors of Peter G. Mikhael

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

All Works

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12 of 12 papers shown

1.

Kilgore, Henry R., Peter G. Mikhael, Lena K. Afeyan, et al.. (2025). Protein codes promote selective subcellular compartmentalization. Science. 387(6738). 1095–1101. 25 indexed citations breakdown →

2.

Simon, Judit, et al.. (2024). Significance of Image Reconstruction Parameters for Future Lung Cancer Risk Prediction Using Low-Dose Chest Computed Tomography and the Open-Access Sybil Algorithm. Investigative Radiology. 60(5). 311–318. 1 indexed citations

3.

Mikhael, Peter G., Jeremy Wohlwend, Adam Yala, et al.. (2023). Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography. Journal of Clinical Oncology. 41(12). 2191–2200. 114 indexed citations breakdown →

4.

Adams, Scott, Peter G. Mikhael, Jeremy Wohlwend, et al.. (2023). Artificial Intelligence and Machine Learning in Lung Cancer Screening. Thoracic surgery clinics/Thorac. surg. clin.. 33(4). 401–409. 16 indexed citations

5.

Kilgore, Henry R., Peter G. Mikhael, Kalon J. Overholt, et al.. (2023). Distinct chemical environments in biomolecular condensates. Nature Chemical Biology. 20(3). 291–301. 51 indexed citations

6.

Simon, Judit, Peter G. Mikhael, Jo-Anne O. Shepard, et al.. (2023). Role of sex in lung cancer risk prediction based on single low-dose chest computed tomography. Scientific Reports. 13(1). 18611–18611. 5 indexed citations

7.

Harrison, Jon M., Adam Yala, Peter G. Mikhael, et al.. (2023). Successful Development of a Natural Language Processing Algorithm for Pancreatic Neoplasms and Associated Histologic Features. Pancreas. 52(4). e219–e223. 1 indexed citations

8.

Yala, Adam, Peter G. Mikhael, Constance D. Lehman, et al.. (2022). Optimizing risk-based breast cancer screening policies with reinforcement learning. Nature Medicine. 28(1). 136–143. 57 indexed citations

9.

Yala, Adam, Peter G. Mikhael, Fredrik Strand, et al.. (2021). Toward robust mammography-based models for breast cancer risk. Science Translational Medicine. 13(578). 135 indexed citations

10.

Kim, Geunwon, Peter G. Mikhael, Tawakalitu O. Oseni, & Manisha Bahl. (2020). Ductal carcinoma in situ on digital mammography versus digital breast tomosynthesis: rates and predictors of pathologic upgrade. European Radiology. 30(11). 6089–6098. 7 indexed citations

11.

Sanderson, Sydney M., Peter G. Mikhael, Vijyendra Ramesh, Ziwei Dai, & Jason W. Locasale. (2019). Nutrient availability shapes methionine metabolism in p16/ MTAP -deleted cells. Science Advances. 5(6). eaav7769–eaav7769. 25 indexed citations

12.

Gao, Xia, Sydney M. Sanderson, Ziwei Dai, et al.. (2019). Dietary methionine influences therapy in mouse cancer models and alters human metabolism. Nature. 572(7769). 397–401. 439 indexed citations breakdown →

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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