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ORCIDFatemeh Shah-Mohammadi
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2020 – today
- 2024
[c17]Fatemeh Shah-Mohammadi, Joseph Finkelstein:
Large Language Model-Based Architecture for Automatic Outcome Data Extraction to Support Meta-Analysis. CCWC 2024: 79-85- 2023
- [c16]Fatemeh Shah-Mohammadi, Joseph Finkelstein:
Contextualized Large Language Model-Based Architecture for Outcome Measure Alignment in Clinical Trials. BIBM 2023: 4411-4417 - [c15]Fatemeh Shah-Mohammadi, Joseph Finkelstein:
Combining NLP and Machine Learning for Differential Diagnosis of COPD Exacerbation Using Emergency Room Data. ICIMTH 2023: 525-528 - [c14]Wanting Cui, Fatemeh Shah-Mohammadi, Joseph Finkelstein:
Using Electronic Medical Records and Clinical Notes to Predict the Outcome of Opioid Treatment Program. ICIMTH 2023: 568-571 - [c13]Fatemeh Shah-Mohammadi, Joseph Finkelstein:
NLP-Assisted Differential Diagnosis of Chronic Obstructive Pulmonary Disease Exacerbation. MedInfo 2023: 589-593 - [c12]Fatemeh Shah-Mohammadi, Joseph Finkelstein:
Identification of Subphenotypes of Opioid Use Disorder Using Unsupervised Machine Learning. MIE 2023: 897-898 - 2022
- [c11]Fatemeh Shah-Mohammadi, Joseph Finkelstein:
Using NLP for Differential Diagnosis of Chronic Obstructive Pulmonary Disease Exacerbation. BIBM 2022: 3876-3878 - [c10]Fatemeh Shah-Mohammadi, Wanting Cui, Keren Bachi, Yasmin Hurd, Joseph Finkelstein:
Comparative Analysis of Patient Distress in Opioid Treatment Programs using Natural Language Processing. BIOSIGNALS 2022: 319-326 - [c9]Fatemeh Shah-Mohammadi, Wanting Cui, Keren Bachi, Yasmin Hurd, Joseph Finkelstein:
Using Natural Language Processing of Clinical Notes to Predict Outcomes of Opioid Treatment Program. EMBC 2022: 4415-4420 - 2021
- [j1]Fatemeh Shah-Mohammadi
, Hatem Hussein Enaami, Andres Kwasinski:
Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access. IEEE Open J. Commun. Soc. 2: 719-737 (2021) - [c8]Fatemeh Shah-Mohammadi, Wanting Cui, Joseph Finkelstein:
Comparison of ACM and CLAMP for Entity Extraction in Clinical Notes. EMBC 2021: 1989-1992 - [c7]Fatemeh Shah-Mohammadi, Wanting Cui, Keren Bachi, Yasmin Hurd, Joseph Finkelstein:
Latent COVID-19 Clusters in Patients with Opioid Misuse. ICIMTH 2021: 123-127 - [c6]Fatemeh Shah-Mohammadi, Irena Parvanova, Joseph Finkelstein:
NLP-Assisted Pipeline for COVID-19 Core Outcome Set Identification Using ClinicalTrials.gov. MedInfo 2021: 622-626 - [c5]Fatemeh Shah-Mohammadi, Wanting Cui, Joseph Finkelstein:
Entity Extraction for Clinical Notes, a Comparison Between MetaMap and Amazon Comprehend Medical. MIE 2021: 258-262 - 2020
- [c4]Fatemeh Shah-Mohammadi, Andres Kwasinski:
Fast Learning Cognitive Radios in Underlay Dynamic Spectrum Access: Integration of Transfer Learning into Deep Reinforcement Learning. WTS 2020: 1-7 - [c3]Fatemeh Shah-Mohammadi, Ankita Tondwalkar, Andres Kwasinski:
Queue-aware QoE-based Rate and Power Adaptation Over Underlay Cognitive Radio Networks: Cross-Layer Design. WTS 2020: 1-7
2010 – 2019
- 2018
- [c2]Fatemeh Shah-Mohammadi, Andres Kwasinski:
QoE-Driven Integrated Heterogeneous Traffic Resource Allocation Based on Cooperative Learning for 5G Cognitive Radio Networks. 5G World Forum 2018: 244-249 - [c1]Fatemeh Shah-Mohammadi, Andres Kwasinski:
Deep Reinforcement Learning Approach to QoE-Driven Resource Allocation for Spectrum Underlay in Cognitive Radio Networks. ICC Workshops 2018: 1-6 - [i1]Fatemeh Shah-Mohammadi, Andres Kwasinski:
Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access. CoRR abs/1806.11038 (2018)
Coauthor Index
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