Medical Big Data AI Start-up Data Analytics Project

Positions available: 3 teams of 3-4 students. Medical research relies heavily on Big Data - large volume of training and testing data is required to build an automatic medical diagnostic tool using advanced Machine Learning techniques. In this project we are looking to determine and build a description of the status quo on the Medical Images datasets that are available worldwide. We are looking to identify, collect and analyze Medial Images datasets that are currently available through government sponsored organization and commercial entities. Students will be responsible for: Identifying Medical Images datasets worldwide. Categorizing the datasets by their coverage, accessibility, eligibility requirements, etc. Collecting and analyzing the datasets. Creating a report on the current availability of Medical Images for research worldwide. More details will be provided during the initial interview. #AI, #Medicine,#InternationalResearch,#PatientsPrivacy, #AIinMedicine

Medical Big Data AI Start-up - Market Research and Analysis Project

Positions available: 5 teams of 3-4 students. Medical research relies heavily on Big Data - large volume of training and testing data is required to build an automatic medical diagnostic tool using advanced Machine Learning techniques. However, presence of Protected Health Information (PHI) in medical images constitutes a significant hurdle to sharing and aggregating data. Due to sheer volume of the datasets, manual removal of PHI is not scalable and building a tool for automatic PHI detection, deletion and masking is crucial. Our company has developed fully automatic system for PHI Deidentification. #AI, #Medicine,#PatientsPrivacy, #AIinMedicine, #BigData

Medical Big Data AI Start-up - Technical Projects

Positions available: 3 teams of 3-4 students. Medical research relies heavily on Big Data - large volume of training and testing data is required to build an automatic medical diagnostic tool using advanced Machine Learning techniques. However, presence of Protected Health Information (PHI) in medical images constitutes a significant hurdle to sharing and aggregating data. Due to sheer volume of the datasets, manual removal of PHI is not scalable and building a tool for automatic PHI detection, deletion and masking is crucial. Our company has developed fully automatic system for PHI Deidentification in Medical Images. More details will be provided during the initial interview. Examples of projects the students could be responsible for: Evaluation of third party NLP Processing solutions Evaluation of third party Image Processing solutions Custom user interfaces Other projects

AI Start-up Customer Segmentation Research for Potential Partnerships

We would like to work with students who are interested in exploring different market segments in medical data markets. Medical research relies heavily on Big Data - large volume of training and testing data is required to build an automatic medical diagnostic tool using advanced Machine Learning techniques. However, presence of Protected Health Information (PHI) in medical images constitutes a significant hurdle to sharing and aggregating data. Due to sheer volume of the datasets, manual removal of PHI is not scalable and building a tool for automatic PHI detection, deletion and masking is crucial. The market is seeing a lot of activity with companies that create big medical data lakes that can be shared with a variety of AI in Medicine startups. There are several segments that we are interested in. The segment will be picked at the beginning of the internship and will depend on students interest and experience.