PeopleofSuperintelligence

Researcher

Emily F. Conant

Also known as Emily Fox Conant, Emily Conant

Emily F. Conant is a breast-imaging researcher whose work applies artificial intelligence to mammographic density and breast-cancer risk prediction. She earned degrees in zoology and medicine at Vermont and Penn, received Penn's 2013 FOCUS Award, and coauthored Deep-LIBRA and MammoFL, methods for estimating breast density from mammograms. She coauthored a 2024 study of risk by molecular subtype and a 2025 study of mammographic texture patterns linked to invasive cancer, false-negative findings, and symptomatic interval cancers; by 2023, she had served as president of the Society of Breast Imaging. As of October 2026, she is an Emeritus Professor CE of Radiology at Penn, was a faculty co-director of a breast-imaging course in January 2026, and is a co-investigator on NIH-funded research into tomosynthesis density and breast-cancer risk.

Works
334
Citations
15,382
h-index
63
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1976–1980

    Zoology and medical degrees

    She earns a B.A. in zoology from the University of Vermont in 1976 and an M.D. from the University of Pennsylvania in 1980.

  2. 2013

    A FOCUS Award

    She receives Penn's 2013 FOCUS Award for the Advancement of Women in Medicine.

  3. 2020

    Deep-LIBRA breast-density estimates

    In 2020, she coauthors Deep-LIBRA, an artificial-intelligence method that estimates breast percentage density from digital mammograms and tests breast-cancer discrimination on an independent dataset.

  4. 2022

    MammoFL across institutions

    In 2022, she coauthors MammoFL, a neural-network method that estimates mammographic breast density across two institutions with federated learning while preserving patient privacy.

  5. By 2023

    Past president of SBI

    By 2023, she is a past president of the Society of Breast Imaging.

  6. June 2024

    Molecular-subtype risk assessment

    In June 2024, she coauthors a study on the feasibility of assessing breast-cancer risk by molecular subtype.

  7. May 2025

    Mammographic texture phenotypes

    In May 2025, she coauthors a study that defines six radiomic clusters and six principal components from mammograms and associates both with higher invasive breast-cancer risk. Its principal components are also positively associated with false-negative findings and symptomatic interval cancers.

  8. As of October 2026

    Emeritus professor at Penn

    As of October 2026, she is an Emeritus Professor CE of Radiology at Penn, where her work includes artificial-intelligence applications in risk prediction and reader performance. In January 2026, she serves as a faculty co-director of Penn's Breast Imaging at the Beach course. In June 2026, she is a co-investigator on a five-year NIH-funded study of tomosynthesis density measures for breast-cancer risk prediction, expected to run through 2031.

Career

  1. Since 1998University of PennsylvaniaEmeritus Professor CE of Radiology
  2. 2016–2018University of Vermont
  3. 1992–1998Thomas Jefferson University
  4. Society of Breast ImagingPresident

Education

  1. 1980University of PennsylvaniaMD
  2. 1976University of VermontBA in Zoology

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Pennsylvania. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes University of Pennsylvania. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Pennsylvania. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Pennsylvania. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Emily Fox Conant | Faculty | About Us | Perelman School of Medicine | Perelman School of Medicine at the University of Pennsylvania med.upenn.edu. Checked 22 October 2026.
  2. BSBR Annual Scientific Meeting 2023 delegate-reg.co.uk. Checked 22 October 2026.
  3. [2011.08001] Deep-LIBRA: Artificial intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment arxiv.org. Checked 22 October 2026.
  4. [2206.05575] MammoFL: Mammographic Breast Density Estimation using Federated Learning arxiv.org. Checked 22 October 2026.
  5. Breast Textures Seen on Mammograms Linked to Cancer Risk | Columbia University Irving Medical Center cuimc.columbia.edu. Checked 22 October 2026.
  6. Researchers Identify Texture Patterns Associated with Breast Cancer Risk | RSNA rsna.org. Checked 22 October 2026.
  7. Radiomic Parenchymal Phenotypes of Breast Texture from Mammography and Association with Risk of Breast Cancer - PMC pmc.ncbi.nlm.nih.gov. Checked 22 October 2026.
  8. Breast Imaging at the Beach - Penn Medicine - Continuing Education (CE) upenn.cloud-cme.com. Checked 22 October 2026.
  9. NIH Grant Supports Research to Improve Prediction of Advanced Breast Cancer Risk | Columbia Department of Radiology columbiaradiology.org. Checked 22 October 2026.