Accurate prognosis and prediction of a patient's current disease state is critical in an ICU. The use of vast amounts of digital medical information can help in predicting the best course of action for the diagnosis and treatment of patients. The proposed technique investigates the strength of using a combination of latent variable models (latent dirichlet allocation) and structured data to transform the information streams into potentially actionable knowledge. In this project, I use Apache Spark to predict mortality among ICU patients so that it can be used as an acuity surrogate to help physicians identify the patients in need of immediate care.
(Master) Thesis template v1.4 for CADMO (Center for Algorithms, Discrete Mathematics and Optimization) at the Swiss Federal Institute of Technology in Zurich (ETH Zürich).
Largely adapted from Adrian Nievergelt's template for the ADPS
(lecture notes) project.
Frank Mousset and Hafsteinn Einarsson (uploaded by LianTze Lim)
EPR paradox as a result of non-force interaction nonlocal quantum objects
This is a LaTeX template (version from 2016 Feb. 17)
for preparing documents for All-Russian Scientific Conference
of the Mathematical Modeling and Boundary Value Problems
[Matem. Mod. Kraev. Zadachi, Samara, Russian Federation].
It was submitted by an author writing for
the 10th All-Russian Scientific Conference with
international participation (MMiKZ’16).
This is a template for a project report in Hindi. It does not do phoenetic conversion by itself but accepts the unicode hindi (Which can be easily generated by online tools such as Google Input Tools). Filled with dummy text for clarity.