Healthcare Innovations and Translational Informatics lab (HITI) @ Emory

Machine learning for Health, Imaging Informatics

About our team

The Healthcare Innovation and Translational Informatics lab (HITI-lab) based out of the Department of Radiology at Emory University works at the intersection Informatics , Artificial Intelligence, and Healthcare. Our projects encompass a wide range of topics from computer vision to natural language processing to radiology workflow. We strive to base each project on a real clinical need and end with implementation of our products into a clinical workflow. Our team works in an interdisciplinary environment comprised of physicians, medical and engineering students, residents, and staff scientists who can each lend their respective expertise.

Please review our Projects page for our current areas of work. If you are interested in collaborating with us contact us via email at emoryhitilab​  AT gmail​ DOT com


Current clinical applications of artificial intelligence in radiology and their best supporting evidence.

Amara Tariq, Saptarshi Purkayastha, Geetha Priya Padmanaban, Elizabeth Krupinski, Hari Trivedi, Imon Banerjee, Judy Wawira Gichoya.

Journal of the American College of Radiology , vol. 17(11), p. 2020

Automatic Breast Cancer Cohort Detection from Social Media for Studying Factors Affecting Patient-Centered Outcomes

Mohammed Ali Al-Garadi, Yuan-Chi Yang, Sahithi Lakamana, Jie Lin, Sabrina Li, Angel Xie, Whitney Hogg-Bremer, Mylin Torres, Imon Banerjee, Abeed Sarker

International Conference on Artificial Intelligence in Medicine, Springer, 2020, pp. 100--110

Prediction of age-related macular degeneration disease using a sequential deep learning approach on longitudinal SD-OCT imaging biomarkers

Imon Banerjee, Luis de Sisternes, Joelle A Hallak, Theodore Leng, Aaron Osborne, Philip J Rosenfeld, Giovanni Gregori, Mary Durbin, Daniel Rubin

Scientific Reports, Nature Publishing Group, 2020, pp. 1--16

Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications

Imon Banerjee, Priyanshu Sinha, Saptarshi Purkayastha, Nazanin Mashhaditafreshi, Amara Tariq, Jiwoong Jeong, Hari Trivedi, Judy W Gichoya

arXiv preprint arXiv:2006.13262, 2020

Phenotyping severity of patient-centered outcomes using clinical notes: A prostate cancer use case

Selen Bozkurt, Rohan Paul, Jean Coquet, Ran Sun, Imon Banerjee, James D Brooks, Tina Hernandez-Boussard

Learning health systems, Wiley Online Library, 2020, pp. e10237

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Mammography dataset creation

This project centers around creating a large dataset of mammograms with ground truth labels extracted from radiology and pathology reports.

AI model development for breast cancer treatment and outcome management

We are developing state-of-the-art deep learning models using mammogram imaging and clinical data. BAC auto segmentation -- using deep learningLongitudinal quantification of BAC in 5 patients.Developed deep learning method for segmenting and quantifyin...

ACR DSI Lab pilot site

Emory is one of the 7 pilot sites for the American College of Radiology AI Lab to work on federated learning. This is to help improve robustness of machine learning models by improving training across different institutions using heterogeneous datasets

Neurofibromatosis Type I AI assisted reporting

Use machine learning to aid reporting of neurofibromatosis 1 MRI images.

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CS584 - Biomedical Image Analysis (Spring 2021)

Emory Graduate Course

With the advancement of deep learning, the field of biomedical imaging has exploded in recent years - but for the uninitiated, even loading nth dimensional data can be a challenge!This course will provide a broad overview of biomedical image analysis a...

CS 170 - Introduction to Programming (Summer 2020, Summer 2021

Emory Undergrad

This course is an introduction to computer science to make serious use of the computer in course work or research. Topics include: fundamental computing concepts, general programming principles, the Unix Operating System, and the Java programming langu...


Dec 10, 2020

Multimodal fusion paper in npj Digital Medicine

Achieving best performance for AI in medical imaging across use cases (like humans) need clinical contextual awareness! Published literature review multi-modal data fusion techniques. (Link)

Dec 10, 2020

Recent paper in JACR

Our paper on “Current clinical applications of #AI in radiology and their best supporting evidence “ just got published in  JACRJournal (Link)

Dec 10, 2020

New collaboration with KheironMedical to develop AI for breast cancer screening on a racially diverse population of patients

Excited to announce our collaboration with KheironMedical to address racial disparities in breast cancer AI, leveraging 300k screening exams including 50k African American women. (Link)

Jan 1, 2020

Reflecting on our work in 2019


Artificial Intelligence Companies Grouped by Modality and Specialty

Last updated May 1st 2020

Supplemental material for Radiology:AI paper


Our lab collaborates with a large number of academic and industrial entities.


Healthcare Innovation and Translational Informatics lab

Machine learning for Health, Imaging Informatics


Department of Radiology and Imaging Sciences

Emory University

1364 Clifton Rd NE Suite AG08
Atlanta, GA 30322
404-712-7118 (ph)
404-686-2226 (fax)

101 Woodruff Circle, Room#4103
Atlanta, GA 30322