5 November Tomorrow is already here: What do telemedicine and AI mean for health professionals and people living with circulatory diseases?: https://crm.world-heart-federation.org/civicrm/event/register?reset=1&id=12
Alex Schoen
Modeling of Supply Chain Systems
https://www.mdpi.com/journal/information/special_issues/Supply_Chain_System
Dear Colleagues,
The increasing complexity and interdependence of supply chain systems, processes acting on these systems, and the networks facilitating the flow of goods and information between supply chain systems call for innovative technologies and methodologies that can efficiently support planning and operation throughout the various phases of the product life cycle. Supply chain systems involve multiple stakeholders with widely varying cooperative and competitive interests. This Special Issue calls for papers that describe new modeling methodologies and case studies that demonstrate how these methodologies can improve the efficiency and resilience of supply chain systems.
Predictive and analytical models that address the challenges and supply chain vulnerabilities of the various phases of the product life cycle are encouraged. Models that focus on the impact of infrastructures and the environment on supply chain processes or on supply chain disruptive events are welcome.
Interested authors are invited to contribute their original, unpublished work. Topics of interest include but are not limited to:
Dr. Zina Ben Miled
Guest Editor
2019 Award Recipients
Landon Crouse and Kyle Haas were recently recognized with the 2019 award for IUPUI. Crouse won in the humanities category (History) and Haas won in the biological/life sciences category (Electrical and Computer Engineering).
Haas’ thesis is entitled, “Transfer Learning for Medication Adherence Prediction from Social Forums Self-Reported Data” and was selected for the award by a panel of faculty from the Electrical and Computer Engineering Department using criteria based on the scope and importance of the research, the strength of his data and statistical analysis, and excellence in writing. Haas’ thesis focused on a machine learning model which uses social media data to predict a patient’s medication adherence.
According to his advisor, Zina Ben Miled, Ph.D., Haas had two summer and one fall internship at Eli Lilly & Company. As part of his research work at Lilly, Haas published two conference papers: one was published in the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics; and the other was published in the 2019 AMIA Summits on Translational Science.
Miled also wrote in a letter of nomination, “The approach he proposed allows the cost-effective identification of patients at-risk of medication non-adherence in a general population. His approach can extend health forums such as Patients-Like-Me with predictive services for medication adherence. He demonstrated and validated his approach for fibromyalgia and diabetes.”
After graduation, Haas joined Eli Lilly and Company as a senior analysist in research data sciences and engineering.
https://graduate.iupui.edu/admissions/financial-support/fellowships-awards/thesis-award.html
https://authors.elsevier.com/a/1aDXq3KEGa5Swn
Artificial Intelligence in Medicine
Dementia can be predicted from EMR routine care data with a level of accuracy suitable for automated pre-screening
Unstructured medical notes improve the accuracy of machine learning models for dementia prediction.
Patients’ health institution affiliations need to be considered in a multi-institution model for dementia.
When Machine Learning and Blockchain meet Supply Chain, Join us in-person or virtually
Join us in person or online
Supply chain visibility is important for cost reduction, market share protection and growth. Mitigating supply chain risks is traditionally addressed from an inbound perspective. This workshop offers an outbound perspective thereby allowing pro-active risk mitigation. The first panel offers a demonstration of a prototype solution developed for a Dow, Inc. case study and a discussion of its application in the context high volume outbound logistics. The second panel is a discussion of potential adoption by other manufacturers, key partnerships and synergies. More info @ MxD
