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相关论文: Explainable AI For Early Detection Of Sepsis

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Sepsis is a leading cause of mortality in intensive care units (ICUs), representing a substantial medical challenge. The complexity of analyzing diverse vital signs to predict sepsis further aggravates this issue. While deep learning…

机器学习 · 计算机科学 2024-05-24 Yuwei Liu , Chen Dan , Anubhav Bhatti , Bingjie Shen , Divij Gupta , Suraj Parmar , San Lee

Sepsis is a major public health concern due to its high morbidity, mortality, and cost. Its clinical outcome can be substantially improved through early detection and timely intervention. By leveraging publicly available datasets, machine…

Sepsis is a severe condition responsible for many deaths in the United States and worldwide, making accurate prediction of outcomes crucial for timely and effective treatment. Previous studies employing machine learning faced limitations in…

Epilepsy is a neurological brain disorder which life threatening and gives rise to recurrent seizures that are unprovoked. It occurs due to the abnormal chemical changes in our brain. Over the course of many years, studies have been…

信号处理 · 电气工程与系统科学 2022-10-13 Muhammad Shoaib Farooq , Aimen Zulfiqar , Shamyla Riaz

We study multiple rule-based and machine learning (ML) models for sepsis detection. We report the first neural network detection and prediction results on three categories of sepsis. We have used the retrospective Medical Information Mart…

机器学习 · 计算机科学 2019-03-07 Avijit Mitra , Khalid Ashraf

Sepsis is a potentially life threatening inflammatory response to infection or severe tissue damage. It has a highly variable clinical course, requiring constant monitoring of the patient's state to guide the management of intravenous…

机器学习 · 计算机科学 2022-02-21 Thesath Nanayakkara , Gilles Clermont , Christopher James Langmead , David Swigon

Artificial Intelligence (AI) plays a crucial role in medical field and has the potential to revolutionize healthcare practices. However, the success of AI models and their impacts hinge on the synergy between AI and medical specialists,…

The prediction of epileptic seizure has always been extremely challenging in medical domain. However, as the development of computer technology, the application of machine learning introduced new ideas for seizure forecasting. Applying…

机器学习 · 计算机科学 2019-10-08 Haotian Liu , Lin Xi , Ying Zhao , Zhixiang Li

Sepsis is a life-threatening and serious global health issue. This study combines knowledge with available hospital data to investigate the potential causes of Sepsis that can be affected by policy decisions. We investigate the underlying…

机器学习 · 计算机科学 2025-02-19 Bruno Petrungaro , Neville K. Kitson , Anthony C. Constantinou

Severe sepsis and septic shock are conditions that affect millions of patients and have close to 50% mortality rate. Early identification of at-risk patients significantly improves outcomes. Electronic surveillance tools have been developed…

计算机与社会 · 计算机科学 2018-09-12 Emilia Apostolova , Tom Velez

Sepsis is a lethal syndrome of organ dysfunction that is triggered by an infection and claims 11 million lives per year globally. Prognostic algorithms based on deep learning have shown promise in detecting the onset of sepsis hours before…

组织与器官 · 定量生物学 2024-08-19 Marco Giordano , Kanika Dheman , Michele Magno

The disease trajectory for clinical sepsis, in terms of temporal cytokine and phenotypic dynamics, can be interpreted as a random dynamical system. The ability to make accurate predictions about patient state from clinical measurements has…

定量方法 · 定量生物学 2020-07-30 Dale Larie , Gary An , Chase Cockrell

Employing a machine learning approach we predict, up to 24 hours prior, a diagnosis of severe sepsis. Strongly predictive models are possible that use only text reports from the Electronic Health Record (EHR), and omit structured numerical…

计算机与社会 · 计算机科学 2017-12-01 Phil Culliton , Michael Levinson , Alice Ehresman , Joshua Wherry , Jay S. Steingrub , Stephen I. Gallant

Sepsis is a life-threatening syndrome with high morbidity and mortality in hospitals. Early prediction of sepsis plays a crucial role in facilitating early interventions for septic patients. However, early sepsis prediction systems with…

机器学习 · 计算机科学 2025-03-20 Anni Zhou , Beyah Raheem , Rishikesan Kamaleswaran , Yao Xie

Guideline-based treatment for sepsis and septic shock is difficult because sepsis is a disparate range of life-threatening organ dysfunctions whose pathophysiology is not fully understood. Early intervention in sepsis is crucial for patient…

Sepsis is a deadly condition affecting many patients in the hospital. Recent studies have shown that patients diagnosed with sepsis have significant mortality and morbidity, resulting from the body's dysfunctional host response to…

机器学习 · 计算机科学 2022-12-14 Ronald Moore , Rishikesan Kamaleswaran

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a major one being acute kidney injury (AKI). For septic patients, approximately 50% develop AKI,…

机器学习 · 计算机科学 2024-12-06 Aleyeh Roknaldin , Zehao Zhang , Jiayuan Xu , Kamiar Alaei , Maryam Pishgar

Sepsis is a poorly understood and potentially life-threatening complication that can occur as a result of infection. Early detection and treatment improves patient outcomes, and as such it poses an important challenge in medicine. In this…

Objective: Epilepsy is one of the most prevalent neurological diseases among humans and can lead to severe brain injuries, strokes, and brain tumors. Early detection of seizures can help to mitigate injuries, and can be used to aid the…

计算机视觉与模式识别 · 计算机科学 2020-11-20 Theekshana Dissanayake , Tharindu Fernando , Simon Denman , Sridha Sridharan , Clinton Fookes

Sepsis is a leading cause of mortality in intensive care units and costs hospitals billions annually. Treating a septic patient is highly challenging, because individual patients respond very differently to medical interventions and there…

人工智能 · 计算机科学 2017-11-28 Aniruddh Raghu , Matthieu Komorowski , Imran Ahmed , Leo Celi , Peter Szolovits , Marzyeh Ghassemi