Artificial intelligence in cancer imaging: Clinical challenges and applications
2019 · CA A Cancer Journal for Clinicians · 1,771 citations
https://doi.org/10.3322/caac.21552
M
Matthew B. Schabath
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Matthew B. Schabath is an academic researcher from Moffitt Cancer Center. The author has contributed to research in topics: Radiomics and Machine Learning in Medical Imaging & Lung Cancer Diagnosis and Treatment & Lung Cancer Treatments and Mutations. The author has an h-index of 65, co-authored 439 publications.
ORCID: 0000-0003-3241-3216Papers by this author
worksLarge-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes
2017 · Nature Genetics · 774 citations
https://doi.org/10.1038/ng.3892
Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study
2017 · PLoS ONE · 660 citations
https://doi.org/10.1371/journal.pone.0177875
Shared heritability and functional enrichment across six solid cancers
2019 · Nature Communications · 123 citations
https://doi.org/10.1038/s41467-018-08054-4
CT imaging features associated with recurrence in non-small cell lung cancer patients after stereotactic body radiotherapy
2017 · Radiation Oncology · 79 citations
https://doi.org/10.1186/s13014-017-0892-y
Peritumoral and intratumoral radiomic features predict survival outcomes among patients diagnosed in lung cancer screening
2020 · Scientific Reports · 79 citations
https://doi.org/10.1038/s41598-020-67378-8
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