1 code implementation • 15 Jan 2024 • Sanaz Hasanzadeh Fard, Mohammad Ghassemi
Traditional approaches to temporal link prediction have focused on finding the aggregation of dynamics of the network as a unified output.
no code implementations • 10 May 2022 • Allen R. Williams, Yoolim Jin, Anthony Duer, Tuka Alhanai, Mohammad Ghassemi
This data is continuously collected and processed nightly into metadata consisting of mileage and time summaries of each discrete trip taken, and a set of behavioral scores describing attributes of the trip (e. g, driver fatigue or driver distraction) so we examine whether it can be used to identify periods of increased risk by successfully classifying trips that occur immediately before a trip in which there was an incident leading to a claim for that driver.
1 code implementation • Findings (EMNLP) 2021 • Hooman Sedghamiz, Shivam Raval, Enrico Santus, Tuka Alhanai, Mohammad Ghassemi
This paper introduces SupCL-Seq, which extends the supervised contrastive learning from computer vision to the optimization of sequence representations in NLP.
1 code implementation • Findings (EMNLP) 2021 • Shivam Raval, Hooman Sedghamiz, Enrico Santus, Tuka Alhanai, Mohammad Ghassemi, Emmanuele Chersoni
Adverse Events (AE) are harmful events resulting from the use of medical products.
2 code implementations • Nature 2016 • Alistair E.W. Johnson, Tom J. Pollard, Lu Shen, Li-wei H. Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, Roger G. Mark
MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital.