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相关论文: Predicting Heart Failure Readmission from Clinical…

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Clinical notes contain a large amount of clinically valuable information that is ignored in many clinical decision support systems due to the difficulty that comes with mining that information. Recent work has found success leveraging deep…

机器学习 · 计算机科学 2019-11-13 Justin R. Lovelace , Nathan C. Hurley , Adrian D. Haimovich , Bobak J. Mortazavi

Hospital readmission, defined as patients being re-hospitalized shortly after discharge, is a critical concern as it impacts patient outcomes and healthcare costs. Identifying patients at risk of readmission allows for timely interventions,…

计算与语言 · 计算机科学 2024-04-09 Rasoul Samani , Mohammad Dehghani , Fahime Shahrokh

We develop a model using deep learning techniques and natural language processing on unstructured text from medical records to predict hospital-wide $30$-day unplanned readmission, with c-statistic $.70$. Our model is constructed to allow…

机器学习 · 统计学 2017-12-21 Erin Craig , Carlos Arias , David Gillman

$\textbf{Objective}$ Develop an automatic diagnostic system which only uses textual admission information from Electronic Health Records (EHRs) and assist clinicians with a timely and statistically proved decision tool. The hope is that the…

计算与语言 · 计算机科学 2017-12-08 Christy Li , Dimitris Konomis , Graham Neubig , Pengtao Xie , Carol Cheng , Eric Xing

Predicting discharge medications right after a patient being admitted is an important clinical decision, which provides physicians with guidance on what type of medication regimen to plan for and what possible changes on initial medication…

计算与语言 · 计算机科学 2017-12-06 Yuan Yang , Pengtao Xie , Xin Gao , Carol Cheng , Christy Li , Hongbao Zhang , Eric Xing

With the increasing availability of patient data, modern medicine is shifting towards prospective healthcare. Electronic health records offer a variety of information useful for clinical patient characterization and the development of…

机器学习 · 计算机科学 2025-05-27 Fabio Azzalini , Tommaso Dolci , Marco Vagaggini

Objective: To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe…

Mitigating risk-of-readmission of Congestive Heart Failure (CHF) patients within 30 days of discharge is important because such readmissions are not only expensive but also critical indicator of provider care and quality of treatment.…

Deep learning techniques have been successfully applied to predict unplanned readmissions of patients in medical centers. The training data for these models is usually based on historical medical records that contain a significant amount of…

计算与语言 · 计算机科学 2020-04-07 Constanza Fierro , Jorge Pérez , Javier Mora

Heart failure (HF) is one of the leading causes of rehospitalization among older adults in the United States. Although clinical notes contain rich, detailed patient information and make up a large portion of electronic health records…

人工智能 · 计算机科学 2026-03-06 Rongjia Zhou , Chengzhuo Li , Carl Yang , Jiaying Lu

Objective: We investigate whether deep learning techniques for natural language processing (NLP) can be used efficiently for patient phenotyping. Patient phenotyping is a classification task for determining whether a patient has a medical…

Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains. However, these architectures have been limited in their ability to support complex prediction problems using insurance…

Intracerebral hemorrhage (ICH) is a life-risking condition characterized by bleeding within the brain parenchyma. ICU readmission in ICH patients is a critical outcome, reflecting both clinical severity and resource utilization. Accurate…

机器学习 · 计算机科学 2025-01-03 Shuheng Chen , Junyi Fan , Armin Abdollahi , Negin Ashrafi , Kamiar Alaei , Greg Placencia , Maryam Pishgar

Unplanned intensive care unit (ICU) readmission rate is an important metric for evaluating the quality of hospital care. Efficient and accurate prediction of ICU readmission risk can not only help prevent patients from inappropriate…

计算与语言 · 计算机科学 2022-01-10 Qiuhao Lu , Thien Huu Nguyen , Dejing Dou

Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to…

机器学习 · 计算机科学 2018-12-27 Ahmed Allam , Mate Nagy , George Thoma , Michael Krauthammer

Machine learning models depend on the quality of input data. As electronic health records are widely adopted, the amount of data in health care is growing, along with complaints about the quality of medical notes. We use two prediction…

计算与语言 · 计算机科学 2020-12-10 Chao-Chun Hsu , Shantanu Karnwal , Sendhil Mullainathan , Ziad Obermeyer , Chenhao Tan

Early detection of preventable diseases is important for better disease management, improved inter-ventions, and more efficient health-care resource allocation. Various machine learning approacheshave been developed to utilize information…

机器学习 · 计算机科学 2018-08-16 Jingshu Liu , Zachariah Zhang , Narges Razavian

The intensive care unit (ICU) comprises a complex hospital environment, where decisions made by clinicians have a high level of risk for the patients' lives. A comprehensive care pathway must then be followed to reduce p complications.…

Hospital readmission has become a critical metric of quality and cost of healthcare. Medicare anticipates that nearly $17 billion is paid out on the 20% of patients who are readmitted within 30 days of discharge. Although several…

应用统计 · 统计学 2014-03-14 Issac Shams , Saeede Ajorlou , Kai Yang

A hospital readmission is when a patient who was discharged from the hospital is admitted again for the same or related care within a certain period. Hospital readmissions are a significant problem in the healthcare domain, as they lead to…

机器学习 · 计算机科学 2023-05-16 Eitam Sheetrit , Menachem Brief , Oren Elisha
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