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Mohammad M. Ghassemi
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2020 – today
- 2024
- [j5]Reza Khanmohammadi
, Sari Saba-Sadiya, Sina Esfandiarpour, Tuka Alhanai
MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs. SN Comput. Sci. 5(5): 628 (2024) - [c34]Hamed Yazdanpanah, Ana Clara Teixeira, Vaishali Marar, Aline Pezente, Mohammad M. Ghassemi:
Data Selective NLMS Outperforms LSTM and Futures for Regional Soybean Prices Forecasting. EUSIPCO 2024: 696-700 - [i16]Reza Khanmohammadi, Simerjot Kaur, Charese H. Smiley, Tuka Alhanai, Ivan Brugere, Armineh Nourbakhsh, Mohammad M. Ghassemi:
The Influence of Biomedical Research on Future Business Funding: Analyzing Scientific Impact and Content in Industrial Investments. CoRR abs/2401.00942 (2024) - [i15]Reza Khanmohammadi, Ahmed I. Ghanem, Kyle Verdecchia, Ryan Hall, Mohamed Elshaikh, Benjamin Movsas, Hassan Bagher-Ebadian, Indrin J. Chetty, Mohammad M. Ghassemi, Kundan Thind:
Iterative Prompt Refinement for Radiation Oncology Symptom Extraction Using Teacher-Student Large Language Models. CoRR abs/2402.04075 (2024) - [i14]Chuheng Wu, Seyed Farokh Atashzar, Mohammad M. Ghassemi, Tuka Alhanai:
An LSTM Feature Imitation Network for Hand Movement Recognition from sEMG Signals. CoRR abs/2405.19356 (2024) - [i13]Mohammad M. Ghassemi, Tuka Alhanai:
Machine-arranged Interactions Improve Institutional Belonging and Cohesion. CoRR abs/2407.19565 (2024) - [i12]Reza Khanmohammadi, Ahmed I. Ghanem, Kyle Verdecchia, Ryan Hall, Mohamed Elshaikh, Benjamin Movsas, Hassan Bagher-Ebadian, Luo Bing, Indrin J. Chetty, Tuka Alhanai, Kundan Thind, Mohammad M. Ghassemi:
Hybrid Student-Teacher Large Language Model Refinement for Cancer Toxicity Symptom Extraction. CoRR abs/2408.04775 (2024) - 2023
- [c33]Lujain Ibrahim, Mohammad M. Ghassemi, Tuka Alhanai:
Do Explanations Improve the Quality of AI-assisted Human Decisions? An Algorithm-in-the-Loop Analysis of Factual & Counterfactual Explanations. AAMAS 2023: 326-334 - [c32]Niloufar Eghbali, Tuka Alhanai
Reinforcement Learning Approach to Sedation and Delirium Management in the Intensive Care Unit. BHI 2023: 1-5 - [c31]Matthew A. Reyna, Edilberto Amorim, Reza Sameni, James Weigle, Andoni Elola, Ali Bahrami Rad, Salman Seyedi, Hyeokhyen Kwon, Wei-Long Zheng, Mohammad M. Ghassemi, Michel J. A. M. van Putten, Jeannette Hofmeijer, Nicolas Gaspard, Adithya Sivaraju, Susan T. Herman, Jong Woo Lee, M. Brandon Westover, Gari D. Clifford:
Predicting Neurological Recovery from Coma After Cardiac Arrest: The George B. Moody PhysioNet Challenge 2023. CinC 2023: 1-4 - [c30]Ana Clara Teixeira
Bayesian Networks Improve Out-of-Distribution Calibration for Agribusiness Delinquency Risk Assessment. ICAIF 2023: 244-252 - [c29]Ana Clara Teixeira
Enhancing Credit Risk Reports Generation using LLMs: An Integration of Bayesian Networks and Labeled Guide Prompting. ICAIF 2023: 340-348 - [i11]Shangyang Min, Mohammad Mahdi Ghassemi, Tuka Alhanai:
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing Tasks. CoRR abs/2306.14572 (2023) - [i10]Reza Khanmohammadi, Tuka Alhanai, Mohammad M. Ghassemi:
The Broad Impact of Feature Imitation: Neural Enhancements Across Financial, Speech, and Physiological Domains. CoRR abs/2309.12279 (2023) - [i9]Reza Khanmohammadi, Mohammad M. Ghassemi, Kyle Verdecchia, Ahmed I. Ghanem, Luo Bing, Indrin J. Chetty, Hassan Bagher-Ebadian, Farzan Siddiqui, Mohamed Elshaikh, Benjamin Movsas, Kundan Thind:
An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology. CoRR abs/2311.02205 (2023) - 2022
- [j4]Wei-Long Zheng
Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning. IEEE Trans. Biomed. Eng. 69(5): 1813-1825 (2022) - [c28]Sari Saba-Sadiya, Tuka Waddah AlHanai
Feature Imitating Networks. ICASSP 2022: 4128-4132 - [c27]Prajjwal Bhattarai
Open-source code repository attributes predict impact of computer science research. JCDL 2022: 16 - [i8]Allen R. Williams, Yoolim Jin, Anthony Duer, Tuka Alhanai, Mohammad M. Ghassemi:
Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach. CoRR abs/2205.04616 (2022) - [i7]Reza Khanmohammadi, Sari Saba-Sadiya, Sina Esfandiarpour, Tuka Alhanai, Mohammad M. Ghassemi:
MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs. CoRR abs/2210.17060 (2022) - 2021
- [j3]Niloufar Eghbali, Tuka Alhanai
Patient-Specific Sedation Management via Deep Reinforcement Learning. Frontiers Digit. Health 3: 608893 (2021) - [c26]Hooman Sedghamiz, Shivam Raval, Enrico Santus, Tuka Alhanai, Mohammad M. Ghassemi:
SupCL-Seq: Supervised Contrastive Learning for Downstream Optimized Sequence Representations. EMNLP (Findings) 2021: 3398-3403 - [c25]Shivam Raval, Hooman Sedghamiz, Enrico Santus, Tuka Alhanai, Mohammad M. Ghassemi, Emmanuele Chersoni:
Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Media. EMNLP (Findings) 2021: 3534-3546 - [c24]Lujain Ibrahim, Mohammad M. Ghassemi, Tuka Alhanai
Modeling Simultaneous Preferences for Age, Gender, Race, and Professional Profiles in Government-Expense Spending: A Conjoint Analysis. HCOMP 2021: 84-96 - [c23]Abhinav Nadh Thirupathi, Tuka Alhanai
A machine learning approach to detect early signs of startup success. ICAIF 2021: 9:1-9:8 - [c22]Sari Sadiya, Tuka Alhanai
Artifact Detection and Correction in EEG data: A Review. NER 2021: 495-498 - [i6]Sari Sadiya, Tuka Alhanai, Mohammad M. Ghassemi:
Artifact Detection and Correction in EEG data: A Review. CoRR abs/2106.13081 (2021) - [i5]Shivam Raval, Hooman Sedghamiz, Enrico Santus, Tuka Alhanai, Mohammad M. Ghassemi, Emmanuele Chersoni:
Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Media. CoRR abs/2109.05815 (2021) - [i4]Hooman Sedghamiz, Shivam Raval, Enrico Santus, Tuka Alhanai, Mohammad M. Ghassemi:
SupCL-Seq: Supervised Contrastive Learning for Downstream Optimized Sequence Representations. CoRR abs/2109.07424 (2021) - [i3]Sari Saba-Sadiya, Tuka Alhanai
Feature Imitating Networks. CoRR abs/2110.04831 (2021) - [i2]Reza Khanmohammadi, Mitra Sadat Mirshafiee, Mohammad Mahdi Ghassemi, Tuka Alhanai
Fetal Gender Identification using Machine and Deep Learning Algorithms on Phonocardiogram Signals. CoRR abs/2110.06131 (2021) - 2020
- [j2]Sari Saba-Sadiya
Unsupervised EEG Artifact Detection and Correction. Frontiers Digit. Health 2: 608920 (2020) - [c21]Sari Saba-Sadiya
EEG Channel Interpolation Using Deep Encoder-decoder Networks. BIBM 2020: 2432-2439 - [c20]Armineh Nourbakhsh, Mohammad M. Ghassemi, Steven Pomerville:
SPread: Automated Financial Metric Extraction and Spreading Tool from Earnings Reports. WSDM 2020: 853-856 - [i1]Sari Saba-Sadiya, Tuka Alhanai
EEG Channel Interpolation Using Deep Encoder-decoder Netwoks. CoRR abs/2009.12244 (2020)
2010 – 2019
- 2018
- [b1]Mohammad Mahdi Ghassemi:
Life after death: techniques for the prognostication of coma outcomes after cardiac arrest. Massachusetts Institute of Technology, Cambridge, USA, 2018 - [c19]Mohammad M. Ghassemi, Tuka Al Hanai, M. Brandon Westover, Roger G. Mark, Shamim Nemati:
Personalized Medication Dosing Using Volatile Data Streams. AAAI Workshops 2018: 435-442 - [c18]Mohammad M. Ghassemi, Benjamin Moody, Li-Wei H. Lehman, Christopher Song, Qiao Li, Haoqi Sun, M. Brandon Westover, Gari D. Clifford:
You Snooze, You Win: The PhysioNet/Computing in Cardiology Challenge 2018. CinC 2018: 1-4 - [c17]Mohammad M. Ghassemi, Tuka Al Hanai
How is the Doctor Feeling? ICU Provider Sentiment is Associated with Diagnostic Imaging Utilization. EMBC 2018: 4058-4064 - [c16]Rongmei Lin, Matthew D. Stanley, Mohammad M. Ghassemi, Shamim Nemati:
A Deep Deterministic Policy Gradient Approach to Medication Dosing and Surveillance in the ICU. EMBC 2018: 4927-4931 - [c15]Tuka Al Hanai
Detecting Depression with Audio/Text Sequence Modeling of Interviews. INTERSPEECH 2018: 1716-1720 - 2017
- [c14]Tuka Waddah AlHanai, Mohammad Mahdi Ghassemi:
Predicting Latent Narrative Mood Using Audio and Physiologic Data. AAAI 2017: 948-954 - [c13]Mohammad M. Ghassemi, Willow Jarvis, Tuka Alhanai
An open-source tool for the transcription of paper-spreadsheet data: Code and supplemental materials available online: Https: //github.com/deskool/images to spreadsheets. IEEE BigData 2017: 935-941 - 2016
- [j1]Alistair E. W. Johnson, Mohammad M. Ghassemi, Shamim Nemati, Katherine E. Niehaus, David A. Clifton, Gari D. Clifford:
Machine Learning and Decision Support in Critical Care. Proc. IEEE 104(2): 444-466 (2016) - [c12]Quanzhi Li, Sameena Shah, Mohammad Mahdi Ghassemi, Rui Fang, Armineh Nourbakhsh, Xiaomo Liu:
Using paraphrases to improve tweet classification: Comparing WordNet and word embedding approaches. IEEE BigData 2016: 4014-4016 - [c11]Hao Du, Mohammad M. Ghassemi, Mengling Feng:
The effects of deep network topology on mortality prediction. EMBC 2016: 2602-2605 - [c10]Shamim Nemati, Mohammad M. Ghassemi, Gari D. Clifford:
Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach. EMBC 2016: 2978-2981 - [c9]Shamim Nemati, Mohammad M. Ghassemi, Vaidehi Ambai, Nino Isakadze
Monitoring and detecting atrial fibrillation using wearable technology. EMBC 2016: 3394-3397 - 2015
- [c8]Mohammad Mahdi Ghassemi, Roger G. Mark, Shamim Nemati:
A Visualization of Evolving Clinical Sentiment Using Vector Representations of Clinical Notes. CinC 2015: 629-632 - [c7]Li-Wei H. Lehman, Mohammad M. Ghassemi, Jasper Snoek, Shamim Nemati:
Patient Prognosis from Vital Sign Time Series: Combining Convolutional Neural Networks with a Dynamical Systems Approach. CinC 2015: 1069-1072 - [c6]Mohammad M. Ghassemi, Edilberto Amorim
An enhanced cerebral recovery index for coma prognostication following cardiac arrest. EMBC 2015: 534-537 - [c5]Armineh Nourbakhsh, Xiaomo Liu, Sameena Shah, Rui Fang, Mohammad Mahdi Ghassemi, Quanzhi Li:
Newsworthy Rumor Events: A Case Study of Twitter. ICDM Workshops 2015: 27-32 - 2014
- [c4]Mengling Feng, Mohammad M. Ghassemi, Thomas Brennan, John Ellenberger, Ishrar Hussain, Roger G. Mark:
Big Data for Critical Care with Cloud-based In-Memory Database. AMIA 2014 - [c3]Shamim Nemati, Mohammad M. Ghassemi:
A fast and memory-efficient algorithm for learning and retrieval of phenotypic dynamics in multivariate cohort time series. IEEE BigData 2014: 41-44 - [c2]Mohammad M. Ghassemi, Li-Wei H. Lehman, Jasper Snoek, Shamim Nemati:
Global Optimization Approaches for Parameter Tuning in Biomedical Signal Processing: A Focus of Multi-scale Entropy. CinC 2014: 993-996 - [c1]Mengling Feng, Mohammad M. Ghassemi, Thomas Brennan, John Ellenberger, Ishrar Hussain, Roger G. Mark:
Management and analytic of biomedical big data with cloud-based in-memory database and dynamic querying: a hands-on experience with real-world data. KDD 2014: 1970
Coauthor Index
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last updated on 2024-11-07 21:32 CET by the dblp team
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