Houshang Darabi on Muck Rack

Houshang Darabi

As seen in: MDPI
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Articles

Deep-Learning Model for Mortality Prediction of ICU Patients with Paralytic Ileus

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By Martha Razo, Maryam Pishgar, William Galanter, Houshang Darabi
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Personalized Learning in Virtual Learning Environments Using Students’ Behavior Analysis

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By Houshang Darabi, Rezvan Nazempour
| MDPI
4. Discussion This section discusses the comparison results of actual and calculated learning style features in Q2, Q3, and Q4. We also suggest two strategies for utilizing learners’ learning styles in order to enhance their academic performance. We calculated the difference (absolute value) between the actual LSs for each student and the calculated ones using the proposed approach in Q2, Q3, and Q4. We specified a threshold, compared the difference with the threshold, and classified students.
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A machine learning based model for Out of Hospital cardiac arrest outcome classification and sensitivity analysis

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By Samuel Harford, Houshang Darabi, Somshubra Majumdar, Fazle Karim
| resuscitationjournal.com
To view the full text, please login as a subscribed user or purchase a subscription. Click here to view the full text on ScienceDirect. Fig. 1 Chicago CARES Relevant Data Collection Flow. Fig. 2 Embedded Fully Convolutional Network Architecture. Abstract Background Out-of-hospital cardiac arrest (OHCA) affects nearly 400,000 people each year in the United States of which only 10% survive.
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