“Of all the forms of inequality, injustice in healthcare is the most shocking and inhuman“
~Martin Luther King Jr
About me
I am currently a research scientist in Responsible AI at Google Research in San Francisco, where I focus on responsible methods for applying and evaluating artificial intelligence (AI) to democratize health. I previously co-founded the Calla Health Foundation, which is commercializing my PhD research, and I am a co-founder of GAPhealth Technologies.
Born and raised in Ghana, I was exposed to ways in which inequity in healthcare impacts lives. After completing high school in Ghana, I moved to the United States on a full scholarship to the University of Rochester, in upstate New York, where I pursued a degree in biomedical engineering and a minor in business, with the goal to use technology to improve health inequities.
Following my undergraduate degree, I pursued my PhD at Duke University in Biomedical Engineering and Global Health under Prof. Nimmi Ramanujam. During my PhD, I developed the Callascope device to increase access to cervical cancer screening, together with machine learning-based algorithms for cervical cancer interpretation. I was lucky to have this work widely recognized.
After my PhD, I received the Schmidt Science Fellowship to pursue my postdoc at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), where I was part of the MIT Jameel Clinic for AI & Healthcare with appointments at Prof. David Sontag’s MIT Clinical Machine Learning Lab and Dr. Anthony Samir’s MGH Center for Ultrasound Research and Translation. My research focused on developing generative adversarial networks to improve ultrasound imaging, and a language model-based tool to enable patients to better understand their notes.
Awards
Talks
A few of my recorded talks
TEDx Duke – The invisible Organ
My Ted talk on cervical cancer disparities and the development of the Callascope for cervical cancer screening
Media Features
Ventures
Giving patients, health providers, organizations, and researchers telehealth and health data tracking software tools powered by data analytics.
While I am no longer part of Calla Health, I support the work partially based on my PhD research, dedicated to improving the lives of women through technological innovations.
Sample publications
A full list of my publications can be found on my Google Scholar Profile
Machine Learning for Colposcopy
Asiedu, M.N., Simhal, A., Chaudhary, U., Mueller, J.L., Lam, C.T., Schmitt, J.W., Venegas, G., Sapiro, G. and Ramanujam, N., 2018. Development of algorithms for automated detection of cervical pre-cancers with a low-cost, point-of-care, pocket colposcope. IEEE Transactions on Biomedical Engineering, 66(8), pp.2306-2318.
Imaging Device for Cervical Cancer Screening
Asiedu, M.N., Agudogo, J., Krieger, M.S., Miros, R., Proeschold-Bell, R.J., Schmitt, J.W. and Ramanujam, N., 2017. Design and preliminary analysis of a vaginal inserter for speculum-free cervical cancer screening. PloS one, 12(5), p.e0177782.
Large Language Models for Clinical Notes
Mannhardt N, Bondi-Kelly E, Lam B, O’Connell C, Asiedu M, Mozannar H, Agrawal M, Buendia A, Urman T, Riaz IB, Ricciardi CE. Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study. arXiv preprint arXiv:2401.09637. 2024 Jan 17.
ML Fairness for Global Health
Asiedu, M.N., Dieng, A., Oppong, A., Nagawa, M., Koyejo, S. and Heller, K., 2023. Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa. arXiv preprint arXiv:2304.02190.
Generative AI to Improve Ultrasound Imaging
Asiedu, M.N., Benjamin, A.R., Singh, V.K., Wang, S., Wu, K., Samir, A.E. and Kumar, V.S., 2022, April. A generative adversarial network for ultrasound signal enhancement by transforming low-voltage beamformed radio frequency data to high-voltage data. In Medical Imaging 2022: Ultrasonic Imaging and Tomography (Vol. 12038, pp. 246-254). SPIE.
Memory Efficient Neural Networks for Smart Ultrasound Wearables
Song, Z., Asiedu, M., Wang, S., Li, Q., Ozturk, A., Mittal, V., Schoen Jr, S., Ramaswamy, S., Pierce, T.T., Samir, A.E. and Eldar, Y.C., 2023. Memory-efficient low-compute segmentation algorithms for bladder-monitoring smart ultrasound devices. Scientific Reports, 13(1), p.16450.
Recent and Upcoming Engagements
May 2024 – ICLR Workshop Chair, Vienna, Austria
December 2023 – Program Chair and Panel Moderator, Machine Learning for Health Symposium, New Orleans, USA
October 2023 – Invited Panelist, Non-Academic Career Paths, Biomedical Engineering Society Conference, Seattle, WA
September 2023 – Co-Lead Organizer, Program Chair and Panelist, Deep Learning Indaba Data Science for Health Workshop 2023, Accra, Ghana
May 2023 – Co-organizer and Panelist, Machine Learning for Global Health Workshop, Kigali Rwanda
February 2023 – Invited Speaker, Disparities in Breast and Cervical Cancer Diagnosis, Owkin
Contact
Dr. Mercy Nyamewaa Asiedu 