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Chen and Doryab's poster presented at the 34th AAAI Conference on Artificial Intelligence

Doryab Presents the First Paper on Modeling Biobehavioral Rhythms for Predicting Rehospitalization Risk

ESE Weekly News | September 27th, 2019

The paper titled "Modeling Biobehavioral Rhythms with Passive Sensing in the Wild: A Case Study to Predict Readmission Risk after Pancreatic Surgery" was presented at Ubicomp, the Association for Computing Machinery (ACM) leading conference on ubiquitous and mobile computing.

AAAI 2020 Conference

February 7th-12th, 2020

I presented my research in collaboration with Xi Chen at the 34th AAAI Conference on Artificial Intelligence in New York, New York. The paper proposes a novel approach to improving the accuracy of feature selection, specifically in data sets with large feature sets and a small number of data points. Existing methods of feature selection typically do not achieve high accuracy. The approach presented optimizes feature selection through Frequent Pattern Growth algorithm to identify frequently occurring sets that appear among the top features selected.

Find the paper here: Optimizing the Feature Selection Process for Better Accuracy in Datasets with a Large Number of Features

Doryab's Paper on the Estimation of Symptom Severity During Chemotherapy from Passively Sensed Data Selected as the Best Cancer Informatics Paper by International Medical Informatics Association

ESE Weekly News | September 20th, 2019

The Editorial Board of the 2019 IMIA Yearbook of Medical Informatics selected article entitled: "Estimation of symptom severity during chemotherapy from passively sensed data: Exploratory study" which was led by Dr. Afsaneh Doryab for listing in the 2019 edition of the Yearbook as one of the best articles published in 2018 in the ‘Cancer Informatics’ subfield of medical informatics.

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