# Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/feasibility-of-blood-testing-combined-with-pet-ct-to-screen-for-cancer-and-guide/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Anne Marie Lennon,Adam H. Buchanan,Isaac Kinde,Andrew Warren,Ashley Honushefsky,Ariella Cohain,David H. Ledbetter,Fred Sanfilippo,Kathleen Sheridan,Dillenia Rosica,Christian S. Adonizio,Hee Jung Hwang,Kamel Lahouel,Joshua D. Cohen,Christopher Douville,Aalpen A. Patel,Leonardo N. Hagmann,David D.K. Rolston,Nirav Malani,Shibin Zhou,Chetan Bettegowda,David L. Diehl,Bobbi Urban,Christopher D. Still,Lisa Kann,Julie Woods,Zachary Salvati,Joseph Vadakara,Rosemary Leeming,Prianka Bhattacharya,Carroll N. Walter,Alex Parker,Christoph Lengauer,Alison P. Klein,Cristian Tomasetti,Elliot K. Fishman,Ralph H. Hruban,Kenneth W. Kinzler,Bert Vogelstein,Nickolas Papadopoulos |
| Citations | 675 |
| DOI | 10.1126/science.abb9601 |
| Fields | Biochemistry, Genetics and Molecular Biology,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/7509949 |
| OpenAlex ID | https://openalex.org/W3020301997 |
| PMID | 32345712 |
| Type | article |
| Year | 2020 |

## Paper authors

- [David L. Diehl](https://scholariq.org/researchers/david-l-diehl/)

## Paper journal

- [Science](https://scholariq.org/journals/science/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Cancer Genomics and Diagnostics](https://scholariq.org/topics/cancer-genomics-and-diagnostics/)
- [Medical Imaging Techniques and Applications](https://scholariq.org/topics/medical-imaging-techniques-and-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.