日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Explainable multimodal deep learning models for variable-length sequences in critically ill patients

针对危重患者可变长度序列的可解释多模态深度学习模型

Martin, Jennifer; Afshar, Majid; Afshar, Askar Safipour; Caskey, John; Dligach, Dmitriy; Gao, Yanjun; Gao, Jifan; Chen, Guanhua; Mayampurath, Anoop; Churpek, Matthew M

Designing a Substance Misuse Data Dashboard for Overdose Fatality Review Teams: User-Centered Design Approach

为过量用药死亡审查小组设计药物滥用数据仪表盘:以用户为中心的设计方法

Pisani, Marie; Oguss, Madeline K; Dickson-Gomez, Julia; Kostelac, Constance; Parry, Amy; Moss, Starr; Salisbury-Afshar, Elizabeth; Patterson, Brian; Spigner, Michael; Gussick, Megan; Krautkramer, Alison; Gruenloh, Timothy; Safipour Afshar, Askar; Gupta, Preeti; Mayampurath, Anoop; Afshar, Majid

Identification of Clinical Phenotypes Among People with HIV Using Electronic Health Record Data

利用电子健康记录数据识别艾滋病毒感染者的临床表型

Mayampurath, Anoop; Isakka, Sheriff; Mason, Joseph A; Nycklemoe, Samuel; Friedman, Eleanor E; Ridgway, Jessica P

Evaluating clinical AI summaries with large language models as judges

使用大型语言模型作为评判者来评估临床人工智能摘要

Croxford, Emma; Gao, Yanjun; First, Elliot; Pellegrino, Nicholas; Schnier, Miranda; Caskey, John; Oguss, Madeline; Wills, Graham; Chen, Guanhua; Dligach, Dmitriy; Churpek, Matthew M; Mayampurath, Anoop; Liao, Frank; Goswami, Cherodeep; Wong, Karen K; Patterson, Brian W; Afshar, Majid

MoMA: a mixture-of-multimodal-agents architecture for enhancing clinical prediction modelling

MoMA:一种用于增强临床预测建模的多模态代理混合架构

Gao, Jifan; Rahman, Mahmudur; Caskey, John; Oguss, Madeline; O'Rourke, Ann; Brown, Randall; Stey, Anne; Mayampurath, Anoop; Churpek, Matthew M; Chen, Guanhua; Afshar, Majid

Machine Learning for Predicting Critical Events Among Hospitalized Children

利用机器学习预测住院儿童的危重事件

Strutz, Sierra; Liang, Huan; Carey, Kyle; Bashiri, Fereshteh; Jani, Priti; Gilbert, Emily; Fitzgerald, Julie L; Kuehnel, Nicholas; Dewan, Maya; Sanchez-Pinto, L Nelson; Edelson, Dana; Afshar, Majid; Churpek, Matthew; Mayampurath, Anoop

Integrating multiple data sources to predict all-cause readmission or mortality in patients with substance misuse

整合多个数据源以预测药物滥用患者的全因再入院率或死亡率

Gruenloh, Tim; Gupta, Preeti; Afshar, Askar Safipour; Oguss, Madeline; Salisbury-Afshar, Elizabeth; Pisani, Marie; Westergaard, Ryan P; Spigner, Michael; Gussick, Megan; Churpek, Matthew; Afshar, Majid; Mayampurath, Anoop

Multicenter Development and Validation of a Multimodal Deep Learning Model to Predict Moderate to Severe AKI

多中心开发和验证用于预测中重度急性肾损伤的多模态深度学习模型

Koyner, Jay L; Martin, Jennie; Carey, Kyle A; Caskey, John; Edelson, Dana P; Mayampurath, Anoop; Dligach, Dmitriy; Afshar, Majid; Churpek, Matthew M

Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: Observational Cohort Study

比较多模态深度学习方法预测病房患者临床恶化:观察性队列研究

Kotula, Charles A; Martin, Jennie; Carey, Kyle A; Edelson, Dana P; Dligach, Dmitriy; Mayampurath, Anoop; Afshar, Majid; Churpek, Matthew M

Explaining alerts from a pediatric risk prediction model using clinical text

使用临床文本解释儿科风险预测模型发出的警报

Nycklemoe, Samuel; Devarapu, Sriharsha; Gao, Yanjun; Carey, Kyle; Kuehnel, Nicholas; Munjal, Neil; Jani, Priti; Churpek, Matthew; Dligach, Dmitriy; Afshar, Majid; Mayampurath, Anoop