Hsu, William

Mammographic classification of interval breast cancers and artificial intelligence performance.

Citation
Yu TT, Hoyt AC, Joines MM, Fischer CP, Yaghmai N, Chalfant JS, Chow L, Mortazavi S, Sears CD, Sayre J, Elmore JG, Hsu W, Milch HS. Mammographic classification of interval breast cancers and artificial intelligence performance. J Natl Cancer Inst. 2025 Aug 1;117(8):1627-1638. doi: 10.1093/jnci/djaf103. PMID: 40249223; PMCID: PMC12342771.
Principal Investigator
Hsu, William
Hoyt, Anne C
Project Name
Using Artificial Intelligence to Support Efficient Same-Day Diagnostic Imaging in Breast Cancer Screening

Risk-stratified screening: A simulation study of scheduling templates on daily mammography recalls.

Citation
Lin Y, Hoyt AC, Manuel VG, Inkelas M, Ayvaci MUS, Ahsen ME, Hsu W. Risk-stratified screening: A simulation study of scheduling templates on daily mammography recalls. J Am Coll Radiol. 2025 Mar;22(3):297-306. doi: 10.1016/j.jacr.2024.12.010. PMID: 40044308; PMCID: PMC11925393.
Principal Investigator
Hsu, William
Hoyt, Anne C
Project Name
Using Artificial Intelligence to Support Efficient Same-Day Diagnostic Imaging in Breast Cancer Screening

Artificial Intelligence Tools to Improve Provider Effectiveness and Patient Outcomes

Event Date
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Artificial intelligence (AI) consistently ranks as the most exciting emerging technology among clinicians, healthcare executives, and researchers, due to its potential to transform healthcare delivery. AI is becoming increasingly important for its potential to enhance clinician productivity, improve quality of care, and increase patients’ engagement in their own care. It also has the potential to streamline patient access to care and personalize medical treatments by leveraging analytics to mine significant, previously untapped stores of unstructured clinical data.

External validation of a commercial artificial intelligence algorithm on a diverse population for detection of false negative breast cancers.

Citation
Plimpton SR, Milch H, Sears C, Chalfant J, Hoyt A, Fischer C, Hsu W, Joines M. External validation of a commercial artificial intelligence algorithm on a diverse population for detection of false negative breast cancers. J Breast Imaging. 2024 Oct 14:wbae058. doi: 10.1093/jbi/wbae058. Epub ahead of print. PMID: 39401322.
Principal Investigator
Hsu, William
Hoyt, Anne C
Project Name
Using Artificial Intelligence to Support Efficient Same-Day Diagnostic Imaging in Breast Cancer Screening

Using discrete event simulation to design and assess an AI-aided workflow for same-day diagnostic testing of women undergoing breast screening.

Citation
Lin Y, Hoyt AC, Manuel VG, Inkelas M, Hsu W. Using discrete event simulation to design and assess an AI-aided workflow for same-day diagnostic testing of women undergoing breast screening. AMIA Jt Summits Transl Sci Proc. 2024 May 31;2024:314-323. PMID: 38827101; PMCID: PMC11141813.
Principal Investigator
Hsu, William
Hoyt, Anne C
Project Name
Using Artificial Intelligence to Support Efficient Same-Day Diagnostic Imaging in Breast Cancer Screening