Custom Big Data and AI Applications

Artificial intelligence, machine learning and big data analytics are the heart and soul of all our solutions.  We innovate on developing robust and efficient methods to empower systems that make our society a better place.


Our areas of innovation are in deep learning for Natural Language Processing, multi-modal deep learning to combine fundamentally different types of data together, engaging both reinforcement learning and transfer learning.  

We apply these principles and tools to a variety of social issues and concerns. Some of our work in this area indluceks:

Mackey TK, Bekki H, Matsuzaki T, Mizushima H.  Examining the Potential for Blockchain Technology to Meet the Needs of 21st Century Japanese Healthcare. J Med Internet Res. 2019; in press 

Mackey TK, Shah N, Miyachi K, Short J, Clauson K. A Framework Proposal for Blockchain-Based Scientific Publishing Using Shared Governance. Front. Blockchain, 15 November 2019 | https://doi.org/10.3389/fbloc.2019.00019

 

Xu Q, Li J, Cai M, Mackey TK. Use of Machine Learning to Detect Wildlife Product Promotion and Sales on Twitter. Front. Big Data. 2019; https://doi.org/10.3389/fdata.2019.00028.

 

Li J, Xu Q, Shah N, Mackey TK. Detection and Characterization of Illicit Digital Drug Dealers on Instagram using Machine Learning. J Med Internet Res. 2019; 21(6):e13803.

 

Mackey TK, Kuo TT, Gummadi B, Clauson K, Church G, Grishin D, Obbad K, Barkovich R, Palombini M. ‘Fit-for-Purpose?’ – Challenges and Opportunities for Applications of Blockchain Technology in the Future of Healthcare. BMC Med. 2019;17:68.

 

Mackey TK.  Opioids and the Internet:  Convergence of Technology and Policy Issues to Address the Illicit Online Sales of Opioids. Health Services Insights. 2018;11.

 

Clauson K, Breeden EA, Davidson C, Mackey TK. Leveraging Blockchain Technology to Enhance Supply Chain Management in Healthcare: An Exploration of Challenges and Opportunities in the Health Supply Chain. Blockchain in Healthcare Today. 2018;1(1).

 

Mackey TK, Kalyanam J. Detection of Illicit Online Sales of Fentanyls via Twitter. F1000. 2017;6:1937

 

Mackey TK, Kalyanam J, Katsuki T, Lanckriet G. Twitter-Based Detection of Illegal Online Sale of Prescription Opioid. Am J. Pub Health. 2017;107:1910-1915.

 

Kalyanam J, Mackey TK. A Review of Digital Surveillance Methods and Approaches to Combat Prescription Drug Abuse. Curr Addict Rep. 2017;4(4):397-409.

 

Tringale K, Marshall D, Mackey TK, Connor M, Murphy J, Hattangadi-Gluth J. Types and Distribution of Payments from Industry to Physicians in 2015. JAMA. 2017;317(17):1774-1784.

 

Mackey TK, Nayyar G. A Review of Existing and Emerging Digital Technologies to Combat the Global Fake Medicines Trade. Expert Opin Drug Saf. 2017;16(5):587-602. [named as a top Blockchain academic paper during the Blockchain Connect Conference Academic 2019, SV Insight] 

 

Cuomo RE, Mackey TK. The Availability of Essential Cancer Medication: An Analysis of National Formularies. J Cancer Policy. 2017;12:49-54.

 

Kalyanam J, Katsuki T, Lanckriet G, Mackey TK. Exploring Trends of Nonmedical use of Prescription Drugs and Polydrug Abuse in the Twittersphere Using Unsupervised Machine Learning. Addict Behav. 2017;65:289-295.

 

Marshall D, Moy B, Jackson M, Mackey TK, Hattangadi-Gluth J. Distribution and Patterns of Industry-related Payments to Oncologists in 2014. J Natl Cancer Inst. 2016;108(12). 

 

Katsuki T, Mackey TK, Cuomo RE. Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies:  Analysis of Twitter Data. J Med Internet Res. 2015;17(12):e280.

 

Mackey TK, *Schoenfeld V. Going "Social" to Access Experimental and Potentially Life-Saving Treatment:  An Assessment of the Policy and Online Patient Advocacy Environment for Expanded Access. BMC Medicine. 2016;14:17.

 

Cuomo RE, Mackey TK, Stigler P. The Economics of Counterfeit Avastin: A Geospatial and Statistical Analysis of Demographic Correlates to FDA Warning Letters. Pharmacoepidemiol Drug Saf. 2015;24(7):748-756.

 

© 2019 S-3 Research, LLC.