December 1, 2019

Four Research Abstracts Accepted and to be Presented @ RSNA 2019

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Four Research Abstracts Accepted and to be Presented @ RSNA 2019

Topics include AI generalization, early cancer detection, data augmentation using GANs, and novel 3D synthetic mammogram algorithms

To learn more, stop by our RSNA booth #10123 in the AI Showcase pavilion or check out our abstracts by clicking on Learn More.

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October 28, 2019

DeepHealth Featured on StartHub as Startup to Watch

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DeepHealth Featured on StartHub as Startup to Watch

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October 15, 2019

DeepHealth Receives $225,000 for Phase I National Science Foundation SBIR Grant

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DeepHealth Receives $225,000 for Phase I National Science Foundation SBIR Grant

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October 11, 2019

Invited Panelist at ASCO’s Global Summit on Innovation in Cancer

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Invited Panelist at ASCO’s Global Summit on Innovation in Cancer

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September 19, 2019

DeepHealth Awarded $2.1M for Phase I/II National Institutes of Health SBIR Grant

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DeepHealth Awarded $2.1M for Phase I/II National Institutes of Health SBIR Grant

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September 10, 2019

Research Paper Accepted @ 2019 NeurIPS Fair Machine Learning for Health Workshop: "Validation of a Deep Learning Mammography Model in a Population with Low Screening Rates"

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Research Paper Accepted @ 2019 NeurIPS Fair Machine Learning for Health Workshop: "Validation of a Deep Learning Mammography Model in a Population with Low Screening Rates"

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November 28, 2018

Research Abstract Presented at RSNA 2018: "Improved Performance of Machine Learning-Based Analysis of Mammography by Using Digital Breast Tomosynthesis Versus 2D Mammography."

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Research Abstract Presented at RSNA 2018: "Improved Performance of Machine Learning-Based Analysis of Mammography by Using Digital Breast Tomosynthesis Versus 2D Mammography."

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November 2, 2018

Industry Talk Presented at Radiology Partners AI Summit: “Deep Learning for Screening Mammography”

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Industry Talk Presented at Radiology Partners AI Summit: “Deep Learning for Screening Mammography”

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September 16, 2018

Keynote Presentation at Breast Imaging Analysis @ MICCAI 2018:  “Towards Clinically Viable AI for Screening Mammography”

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Keynote Presentation at Breast Imaging Analysis @ MICCAI 2018:  “Towards Clinically Viable AI for Screening Mammography”

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September 16, 2018

Best Paper Award at Breast Imaging Analysis @ MICCAI 2018: "Conditional Infilling GANs for Data Augmentation in Mammogram Classification"

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Best Paper Award at Breast Imaging Analysis @ MICCAI 2018: "Conditional Infilling GANs for Data Augmentation in Mammogram Classification"

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May 24, 2018

Industry Panel Moderator at REWORK Deep Learning in Healthcare Summit: "The Future of Cancer Treatment with the Application of Deep Learning"

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Industry Panel Moderator at REWORK Deep Learning in Healthcare Summit: "The Future of Cancer Treatment with the Application of Deep Learning"

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March 4, 2018

Research Abstract Presented at Biomedical and Health Informatics Conference 2018:  "Towards Finding the 'Needle in the Haystack': DeepHealth's Entry to the Mammography DREAM Challenge"

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Research Abstract Presented at Biomedical and Health Informatics Conference 2018:  "Towards Finding the 'Needle in the Haystack': DeepHealth's Entry to the Mammography DREAM Challenge"

Presented in Special Session 1: Building the Biggest Challenge in Digital Mammography

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March 4, 2018

Industry Panel Member at Biomedical and Health Informatics Conference 2018: "The Role of AI in Connected Health"

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Industry Panel Member at Biomedical and Health Informatics Conference 2018: "The Role of AI in Connected Health"

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December 14, 2017

Selected to be in Cohort of Pulse@MassChallenge (now MassChallenge HealthTech) - 6% Acceptance Rate

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Selected to be in Cohort of Pulse@MassChallenge (now MassChallenge HealthTech) - 6% Acceptance Rate

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October 17, 2017

Research Paper Presented at Deep Learning in Medical Image Analysis @ MICCAI 2017: "A Multi-Scale CNN and Curriculum Learning Strategy for Mammogram Classification"

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Research Paper Presented at Deep Learning in Medical Image Analysis @ MICCAI 2017: "A Multi-Scale CNN and Curriculum Learning Strategy for Mammogram Classification"

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