Leveraging prior knowledge in machine intelligence to improve lesion diagnosis for early cancer detection
Leveraging prior knowledge in machine intelligence can enhance lesion diagnosis, resolve the ambiguity of IDLs interpreted by experts, and improve the effectiveness of LdCT screening for early-stage cancers.
Authors
- Yongfeng Gao
- Shaojie Chang (ORCID: https://orcid.org/0000-0003-0550-9650)
- Weiguo Cao (ORCID: https://orcid.org/0000-0001-9181-6133)
- Jela Bandovic (ORCID: https://orcid.org/0000-0001-8775-5155)
- Perry Joseph Pickhardt (ORCID: https://orcid.org/0000-0002-5534-8202)
- Lihong C. Li
- Zhengrong Jerome Liang
- Michael J. Reiter
- Almas F. Abbasi
- Licheng R. Kuo
- M.J. Pomeroy
Institutions
- Mayo Clinic (US)
- University of Wisconsin–Madison (US)
- College of Staten Island (US)
- City University of New York (US)
- Stony Brook University (US)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1002/mp.17841
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36