no code implementations • 10 Jul 2024 • Yingbo Ma, Yukyeong Song, Jeremy A. Balch, Yuanfang Ren, Divya Vellanki, Zhenhong Hu, Meghan Brennan, Suraj Kolla, Ziyuan Guan, Brooke Armfield, Tezcan Ozrazgat-Baslanti, Parisa Rashidi, Tyler J. Loftus, Azra Bihorac, Benjamin Shickel
Additionally, we identified several challenges associated with integrating AI training into the medical education program, including a lack of guidelines to define medical students AI literacy, a perceived lack of proven clinical value, and a scarcity of qualified instructors.
no code implementations • 18 Apr 2024 • Yuanfang Ren, Chirayu Tripathi, Ziyuan Guan, Ruilin Zhu, Victoria Hougha, Yingbo Ma, Zhenhong Hu, Jeremy Balch, Tyler J. Loftus, Parisa Rashidi, Benjamin Shickel, Tezcan Ozrazgat-Baslanti, Azra Bihorac
Given the sheer volume of surgical procedures and the significant rate of postoperative fatalities, assessing and managing surgical complications has become a critical public health concern.
no code implementations • 10 Apr 2024 • Yingbo Ma, Suraj Kolla, Zhenhong Hu, Dhruv Kaliraman, Victoria Nolan, Ziyuan Guan, Yuanfang Ren, Brooke Armfield, Tezcan Ozrazgat-Baslanti, Jeremy A. Balch, Tyler J. Loftus, Parisa Rashidi, Azra Bihorac, Benjamin Shickel
To harness the interconnected relationships between medical time series and clinical notes, the framework equips a global contrastive loss, aligning a patient's multimodal feature representations with the corresponding discharge summaries.
no code implementations • 9 Apr 2024 • Yonggi Park, Yuanfang Ren, Benjamin Shickel, Ziyuan Guan, Ayush Patela, Yingbo Ma, Zhenhong Hu, Tyler J. Loftus, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Azra Bihorac
Federated learning models achieved comparable AUROC performance to central learning models, except for prolonged ICU stay, where the performance of federated learning models was slightly higher than central learning models at UFH GNV center, but slightly lower at UFH JAX center.
no code implementations • 6 Mar 2024 • Yingbo Ma, Suraj Kolla, Dhruv Kaliraman, Victoria Nolan, Zhenhong Hu, Ziyuan Guan, Yuanfang Ren, Brooke Armfield, Tezcan Ozrazgat-Baslanti, Tyler J. Loftus, Parisa Rashidi, Azra Bihorac, Benjamin Shickel
The breadth, scale, and temporal granularity of modern electronic health records (EHR) systems offers great potential for estimating personalized and contextual patient health trajectories using sequential deep learning.
no code implementations • 6 Feb 2024 • Esra Adiyeke, Yuanfang Ren, Benjamin Shickel, Matthew M. Ruppert, Ziyuan Guan, Sandra L. Kane-Gill, Raghavan Murugan, Nabihah Amatullah, Britney A. Stottlemyer, Tiffany L. Tran, Dan Ricketts, Christopher M Horvat, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti
We trained local models for each site (UFH Model trained on UFH, UPMC Model trained on UPMC) and a separate model with a development cohort of patients from both sites (UFH-UPMC Model).
no code implementations • 24 Jan 2024 • Darren Liu, Cheng Ding, Delgersuren Bold, Monique Bouvier, Jiaying Lu, Benjamin Shickel, Craig S. Jabaley, Wenhui Zhang, Soojin Park, Michael J. Young, Mark S. Wainwright, Gilles Clermont, Parisa Rashidi, Eric S. Rosenthal, Laurie Dimisko, Ran Xiao, Joo Heung Yoon, Carl Yang, Xiao Hu
Methods: We investigated the performance of three general LLMs in understanding and processing real-world clinical notes.
1 code implementation • 23 Jan 2024 • Muhammad Imran, Jonathan R Krebs, Veera Rajasekhar Reddy Gopu, Brian Fazzone, Vishal Balaji Sivaraman, Amarjeet Kumar, Chelsea Viscardi, Robert Evans Heithaus, Benjamin Shickel, Yuyin Zhou, Michol A Cooper, Wei Shao
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases.
no code implementations • 3 Nov 2023 • Jessica Sena, Mohammad Tahsin Mostafiz, Jiaqing Zhang, Andrea Davidson, Sabyasachi Bandyopadhyay, Ren Yuanfang, Tezcan Ozrazgat-Baslanti, Benjamin Shickel, Tyler Loftus, William Robson Schwartz, Azra Bihorac, Parisa Rashidi
In this study, we evaluated the impact of integrating mobility data collected from wrist-worn accelerometers with clinical data obtained from EHR for developing an AI-driven acuity assessment score.
no code implementations • 3 Nov 2023 • Miguel Contreras, Brandon Silva, Benjamin Shickel, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Ziyuan Guan, Jeremy Balch, Jiaqing Zhang, Sabyasachi Bandyopadhyay, Kia Khezeli, Azra Bihorac, Parisa Rashidi
The acuity state of patients in the intensive care unit (ICU) can quickly change from stable to unstable.
no code implementations • 27 Jul 2023 • Yuanfang Ren, Yanjun Li, Tyler J. Loftus, Jeremy Balch, Kenneth L. Abbott, Shounak Datta, Matthew M. Ruppert, Ziyuan Guan, Benjamin Shickel, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Azra Bihorac
With clustering analysis for vital signs within six hours of admission, patient phenotypes with distinct pathophysiological signatures and outcomes may support early clinical decisions.
no code implementations • 30 Jun 2023 • Subhash Nerella, Sabyasachi Bandyopadhyay, Jiaqing Zhang, Miguel Contreras, Scott Siegel, Aysegul Bumin, Brandon Silva, Jessica Sena, Benjamin Shickel, Azra Bihorac, Kia Khezeli, Parisa Rashidi
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications.
no code implementations • 9 Mar 2023 • Yuanfang Ren, Tyler J. Loftus, Ziyuan Guan, Rayon Uddin, Benjamin Shickel, Carolina B. Maciel, Katharina Busl, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti
We developed algorithms to quantify acute brain dysfunction status including coma, delirium, normal, or death at 12-hour intervals of each ICU admission and to identify acute brain dysfunction phenotypes using continuous acute brain dysfunction status and k-means clustering approach.
no code implementations • 9 Nov 2021 • Benjamin Shickel, Patrick J. Tighe, Azra Bihorac, Parisa Rashidi
Recent deep learning research based on Transformer model architectures has demonstrated state-of-the-art performance across a variety of domains and tasks, mostly within the computer vision and natural language processing domains.
no code implementations • 27 Apr 2020 • Benjamin Shickel, Tyler J. Loftus, Matthew Ruppert, Gilbert R. Upchurch, Tezcan Ozrazgat-Baslanti, Parisa Rashidi, Azra Bihorac
In a longitudinal cohort study of 56, 242 patients undergoing 67, 481 inpatient surgical procedures at a university medical center, we compared deep learning models with random forests for predicting nine common postoperative complications using preoperative, intraoperative, and perioperative patient data.
no code implementations • 27 Apr 2020 • Yuanfang Ren, Jeremy Balch, Kenneth L. Abbott, Tyler J. Loftus, Benjamin Shickel, Parisa Rashidi, Azra Bihorac, Tezcan Ozrazgat-Baslanti
We gathered two single-center, longitudinal electronic health record datasets for 51, 372 adult ICU patients admitted to the University of Florida Health (UFH) Gainesville (GNV) and Jacksonville (JAX).
no code implementations • 27 Apr 2020 • Benjamin Shickel, Parisa Rashidi
Given recent deep learning advancements in highly sequential domains such as natural language processing and physiological signal processing, the need for deep sequential explanations is at an all-time high.
no code implementations • 16 Sep 2019 • Benjamin Shickel, Scott Siegel, Martin Heesacker, Sherry Benton, Parisa Rashidi
In this paper, we present a machine learning framework for the automatic detection and classification of 15 common cognitive distortions in two novel mental health free text datasets collected from both crowdsourcing and a real-world online therapy program.
no code implementations • 25 Apr 2018 • Anis Davoudi, Kumar Rohit Malhotra, Benjamin Shickel, Scott Siegel, Seth Williams, Matthew Ruppert, Emel Bihorac, Tezcan Ozrazgat-Baslanti, Patrick J. Tighe, Azra Bihorac, Parisa Rashidi
In this pilot study, we examined the feasibility of using pervasive sensing technology and artificial intelligence for autonomous and granular monitoring of critically ill patients and their environment in the Intensive Care Unit (ICU).
no code implementations • 28 Feb 2018 • Benjamin Shickel, Tyler J. Loftus, Lasith Adhikari, Tezcan Ozrazgat-Baslanti, Azra Bihorac, Parisa Rashidi
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds.
no code implementations • 4 Aug 2017 • Benjamin Shickel, Martin Heesacker, Sherry Benton, Parisa Rashidi
As the popularity of social media platforms continues to rise, an ever-increasing amount of human communication and self- expression takes place online.
no code implementations • 12 Jun 2017 • Benjamin Shickel, Patrick Tighe, Azra Bihorac, Parisa Rashidi
The past decade has seen an explosion in the amount of digital information stored in electronic health records (EHR).