Zobrazeno 1 - 10
of 527
pro vyhledávání: '"Baslanti TO"'
Autor:
Contreras, Miguel, Kapoor, Sumit, Zhang, Jiaqing, Davidson, Andrea, Ren, Yuanfang, Guan, Ziyuan, Ozrazgat-Baslanti, Tezcan, Nerella, Subhash, Bihorac, Azra, Rashidi, Parisa
Delirium is an acute confusional state that has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection of this condition could lead to more timely interventions and improved health outcomes. While artificial inte
Externí odkaz:
http://arxiv.org/abs/2410.17363
Autor:
Ma, Yingbo, Song, Yukyeong, Balch, Jeremy A., Ren, Yuanfang, Vellanki, Divya, Hu, Zhenhong, Brennan, Meghan, Kolla, Suraj, Guan, Ziyuan, Armfield, Brooke, Ozrazgat-Baslanti, Tezcan, Rashidi, Parisa, Loftus, Tyler J., Bihorac, Azra, Shickel, Benjamin
As more clinical workflows continue to be augmented by artificial intelligence (AI), AI literacy among physicians will become a critical requirement for ensuring safe and ethical AI-enabled patient care. Despite the evolving importance of AI in healt
Externí odkaz:
http://arxiv.org/abs/2407.18939
Autor:
Ren, Yuanfang, Tripathi, Chirayu, Guan, Ziyuan, Zhu, Ruilin, Hougha, Victoria, Ma, Yingbo, Hu, Zhenhong, Balch, Jeremy, Loftus, Tyler J., Rashidi, Parisa, Shickel, Benjamin, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra
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. Existing artificial intelligence (AI) tools for risk survei
Externí odkaz:
http://arxiv.org/abs/2404.16064
Autor:
Ma, Yingbo, Kolla, Suraj, Hu, Zhenhong, Kaliraman, Dhruv, Nolan, Victoria, Guan, Ziyuan, Ren, Yuanfang, Armfield, Brooke, Ozrazgat-Baslanti, Tezcan, Balch, Jeremy A., Loftus, Tyler J., Rashidi, Parisa, Bihorac, Azra, Shickel, Benjamin
Modern electronic health records (EHRs) hold immense promise in tracking personalized patient health trajectories through sequential deep learning, owing to their extensive breadth, scale, and temporal granularity. Nonetheless, how to effectively lev
Externí odkaz:
http://arxiv.org/abs/2404.06723
Autor:
Park, Yonggi, Ren, Yuanfang, Shickel, Benjamin, Guan, Ziyuan, Patela, Ayush, Ma, Yingbo, Hu, Zhenhong, Loftus, Tyler J., Rashidi, Parisa, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra
Background: The accurate prediction of postoperative complication risk using Electronic Health Records (EHR) and artificial intelligence shows great potential. Training a robust artificial intelligence model typically requires large-scale and diverse
Externí odkaz:
http://arxiv.org/abs/2404.06641
Autor:
Adiyeke, Esra, Ren, Yuanfang, Fogel, Shmuel, Rashidi, Parisa, Segal, Mark, Shenkman, Elizabeth A., Bihorac, Azra, Ozrazgat-Baslanti, Tezcan
Background: Acute kidney injury (AKI) is a clinical syndrome affecting almost one fifth of hospitalized patients, as well as more than half of the patients who are admitted to the intensive care unit (ICU). Stratifying AKI patients into groups based
Externí odkaz:
http://arxiv.org/abs/2403.08020
Autor:
Silva, Brandon, Contreras, Miguel, Bandyopadhyay, Sabyasachi, Ren, Yuanfang, Guan, Ziyuan, Balch, Jeremy, Khezeli, Kia, Baslanti, Tezcan Ozrazgat, Shickel, Ben, Bihorac, Azra, Rashidi, Parisa
Assessing acute brain dysfunction (ABD), including delirium and coma in the intensive care unit (ICU), is a critical challenge due to its prevalence and severe implications for patient outcomes. Current diagnostic methods rely on infrequent clinical
Externí odkaz:
http://arxiv.org/abs/2403.07201
Autor:
Siegel, Scott, Zhang, Jiaqing, Bandyopadhyay, Sabyasachi, Nerella, Subhash, Silva, Brandon, Baslanti, Tezcan, Bihorac, Azra, Rashidi, Parisa
Despite the importance of closely monitoring patients in the Intensive Care Unit (ICU), many aspects are still assessed in a limited manner due to the time constraints imposed on healthcare providers. For example, although excessive visitations durin
Externí odkaz:
http://arxiv.org/abs/2403.06322
Autor:
Ma, Yingbo, Kolla, Suraj, Kaliraman, Dhruv, Nolan, Victoria, Hu, Zhenhong, Guan, Ziyuan, Ren, Yuanfang, Armfield, Brooke, Ozrazgat-Baslanti, Tezcan, Loftus, Tyler J., Rashidi, Parisa, Bihorac, Azra, Shickel, Benjamin
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. However, learning useful repr
Externí odkaz:
http://arxiv.org/abs/2403.04012
Autor:
Adiyeke, Esra, Ren, Yuanfang, Shickel, Benjamin, Ruppert, Matthew M., Guan, Ziyuan, Kane-Gill, Sandra L., Murugan, Raghavan, Amatullah, Nabihah, Stottlemyer, Britney A., Tran, Tiffany L., Ricketts, Dan, Horvat, Christopher M, Rashidi, Parisa, Bihorac, Azra, Ozrazgat-Baslanti, Tezcan
Background: Acute kidney injury (AKI), the decline of kidney excretory function, occurs in up to 18% of hospitalized admissions. Progression of AKI may lead to irreversible kidney damage. Methods: This retrospective cohort study includes adult patien
Externí odkaz:
http://arxiv.org/abs/2402.04209