no code implementations • 19 May 2023 • Anaelia Ovalle, Mehrab Beikzadeh, Parshan Teimouri, Kai-Wei Chang, Majid Sarrafzadeh
Large language models have been useful in expanding mental health care delivery.
no code implementations • 24 Mar 2023 • Shayan Fazeli, Lionel Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh
Recent advances in remote health monitoring systems have significantly benefited patients and played a crucial role in improving their quality of life.
no code implementations • 16 Nov 2022 • Anaelia Ovalle, Sunipa Dev, Jieyu Zhao, Majid Sarrafzadeh, Kai-Wei Chang
Therefore, ML auditing tools must be (1) better aligned with ML4H auditing principles and (2) able to illuminate and characterize communities vulnerable to the most harm.
1 code implementation • 19 May 2022 • Shayan Fazeli, Alireza Samiei, Thomas D. Lee, Majid Sarrafzadeh
Analyzing and inspecting bone marrow cell cytomorphology is a critical but highly complex and time-consuming component of hematopathology diagnosis.
1 code implementation • 27 Aug 2021 • Sajad Darabi, Shayan Fazeli, Ali Pazoki, Sriram Sankararaman, Majid Sarrafzadeh
Recent literature in self-supervised has demonstrated significant progress in closing the gap between supervised and unsupervised methods in the image and text domains.
1 code implementation • 19 Aug 2021 • Shayan Fazeli, Majid Sarrafzadeh
Topic Modeling refers to the problem of discovering the main topics that have occurred in corpora of textual data, with solutions finding crucial applications in numerous fields.
no code implementations • 12 May 2021 • Kimmo Kärkkäinen, Shayan Fazeli, Majid Sarrafzadeh
We demonstrate the results of our algorithm on publicly-available datasets that contain all different hemorrhage types in various sizes and intensities, and our results are compared to earlier unsupervised and supervised algorithms.
no code implementations • 22 Apr 2021 • Shayan Fazeli, Davina Zamanzadeh, Anaelia Ovalle, Thu Nguyen, Gilbert Gee, Majid Sarrafzadeh
We provide a multi-faceted analysis of critical properties exhibited by these conversations on social media regarding the novel coronavirus pandemic.
1 code implementation • 11 Nov 2020 • Orpaz Goldstein, Mohammad Kachuee, Derek Shiell, Majid Sarrafzadeh
Transferring knowledge in a selective decentralized approach enables models to retain their local insights, allowing for local flavors of a machine learning model.
1 code implementation • 12 Jul 2020 • Yuchao Ma, Andrew T. Campbell, Diane J. Cook, John Lach, Shwetak N. Patel, Thomas Ploetz, Majid Sarrafzadeh, Donna Spruijt-Metz, Hassan Ghasemzadeh
While activity recognition from inertial sensors holds potential for mobile health, differences in sensing platforms and user movement patterns cause performance degradation.
1 code implementation • 9 Jun 2020 • Shayan Fazeli, Majid Sarrafzadeh
Developing and maintaining monitoring panels is undoubtedly the main task in the remote patient monitoring (RPM) systems.
no code implementations • 22 Dec 2019 • Anahita Hosseini, Tyler Davis, Majid Sarrafzadeh
We introduce HTAD, a novel model for diagnosis prediction using Electronic Health Records (EHR) represented as Heterogeneous Information Networks.
no code implementations • 20 Dec 2019 • Mohammad Kachuee, Sajad Darabi, Shayan Fazeli, Majid Sarrafzadeh
GMLP is based on the idea of learning expressive feature combinations (groups) and exploiting them to reduce the network complexity by defining local group-wise operations.
no code implementations • 17 Dec 2019 • Kimmo Kärkkäinen, Mohammad Kachuee, Orpaz Goldstein, Majid Sarrafzadeh
The chosen features should increase the prediction accuracy for a low cost, but determining which features will do that is challenging.
no code implementations • 4 Oct 2019 • Sajad Darabi, Mohammad Kachuee, Majid Sarrafzadeh
In this work, we present a two-step unsupervised representation learning scheme to summarize the multi-modal clinical time series consisting of signals and medical codes into a patient status vector.
no code implementations • 15 Sep 2019 • Orpaz Goldstein, Mohammad Kachuee, Kimmo Karkkainen, Majid Sarrafzadeh
In many real-world scenarios where data is high dimensional, test time acquisition of features is a non-trivial task due to costs associated with feature acquisition and evaluating feature value.
2 code implementations • 11 Aug 2019 • Sajad Darabi, Mohammad Kachuee, Shayan Fazeli, Majid Sarrafzadeh
The data contained in these records are irregular and contain multiple modalities such as notes, and medical codes.
2 code implementations • 22 May 2019 • Mohammad Kachuee, Kimmo Karkkainen, Orpaz Goldstein, Sajad Darabi, Majid Sarrafzadeh
In order to make imputations, we train a simple and effective generator network to generate imputations that a discriminator network is tasked to distinguish.
2 code implementations • 19 Feb 2019 • Mohammad Kachuee, Kimmo Karkkainen, Orpaz Goldstein, Davina Zamanzadeh, Majid Sarrafzadeh
Furthermore, based on the suggested dataset, we provide a comparison of recent and state-of-the-art approaches to cost-sensitive feature acquisition and learning.
no code implementations • 31 Jan 2019 • Anahita Hosseini, Majid Sarrafzadeh
The emergence of continuous health monitoring and the availability of an enormous amount of time series data has provided a great opportunity for the advancement of personal health tracking.
1 code implementation • ICLR 2019 • Mohammad Kachuee, Orpaz Goldstein, Kimmo Karkkainen, Sajad Darabi, Majid Sarrafzadeh
The suggested method acquires features incrementally based on a context-aware feature-value function.
1 code implementation • 3 Nov 2018 • Mohammad Kachuee, Sajad Darabi, Babak Moatamed, Majid Sarrafzadeh
In real-world scenarios, different features have different acquisition costs at test-time which necessitates cost-aware methods to optimize the cost and performance trade-off.
no code implementations • 22 Apr 2018 • Anahita Hosseini, Ting Chen, Wenjun Wu, Yizhou Sun, Majid Sarrafzadeh
To the best of our knowledge, this is the first study to use Heterogeneous Information Network for modeling clinical data and disease diagnosis.
13 code implementations • 19 Apr 2018 • Mohammad Kachuee, Shayan Fazeli, Majid Sarrafzadeh
Electrocardiogram (ECG) can be reliably used as a measure to monitor the functionality of the cardiovascular system.