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Sepsis is a leading cause of mortality and critical illness worldwide. While robust biomarkers for early diagnosis are still missing, recent work indicates that hyperspectral imaging (HSI) has the potential to overcome this bottleneck by…

The analysis of microcirculation images has the potential to reveal early signs of life-threatening diseases like sepsis. Quantifying the capillary density and the capillary distribution in microcirculation images can be used as a…

Computer Vision and Pattern Recognition · Computer Science 2022-05-12 Maged Abdalla Helmy Mohamed Abdou , Trung Tuyen Truong , Eric Jul , Paulo Ferreira

Current machine learning models aiming to predict sepsis from Electronic Health Records (EHR) do not account for the heterogeneity of the condition, despite its emerging importance in prognosis and treatment. This work demonstrates the…

Quantitative Methods · Quantitative Biology 2020-11-24 Zina Ibrahim , Honghan Wu , Ahmed Hamoud , Lukas Stappen , Richard Dobson , Andrea Agarossi

Sepsis is the leading cause of death in non-coronary intensive care units. Moreover, a delay of antibiotic treatment of patients with severe sepsis by only few hours is associated with increased mortality. This insight makes accurate models…

Quantitative Methods · Quantitative Biology 2019-09-26 Shigehiko Schamoni , Holger A. Lindner , Verena Schneider-Lindner , Manfred Thiel , Stefan Riezler

With sepsis remaining a leading cause of mortality, early identification of patients with sepsis and those at high risk of death is a challenge of high socioeconomic importance. Given the potential of hyperspectral imaging (HSI) to monitor…

Sepsis is a life threatening condition that requires timely detection in intensive care settings. Traditional machine learning approaches, including Naive Bayes, Support Vector Machine (SVM), Random Forest, and XGBoost, often rely on manual…

Machine Learning · Computer Science 2025-09-03 Hejiang Cai , Di Wu , Ji Xu , Xiang Liu , Yiziting Zhu , Xin Shu , Yujie Li , Bin Yi

Sepsis is a life-threatening condition which requires rapid diagnosis and treatment. Traditional microbiological methods are time-consuming and expensive. In response to these challenges, deep learning algorithms were developed to identify…

Sepsis is a life-threatening condition with organ dysfunction and is a leading cause of death and critical illness worldwide. Even a few hours of delay in the treatment of sepsis results in increased mortality. Early detection of sepsis…

Background: While machine learning (ML) models are rapidly emerging as promising screening tools in critical care medicine, the identification of homogeneous subphenotypes within populations with heterogeneous conditions such as pediatric…

Sepsis is a life-threatening condition that requires rapid detection and treatment to prevent progression to severe sepsis, septic shock, or multi-organ failure. Despite advances in medical technology, it remains a major challenge for…

Machine Learning · Computer Science 2025-11-11 Atharva Thakur , Shruti Dhumal

With a mortality rate of 5.4 million lives worldwide every year and a healthcare cost of more than 16 billion dollars in the USA alone, sepsis is one of the leading causes of hospital mortality and an increasing concern in the ageing…

Machine Learning · Computer Science 2021-05-12 Margherita Rosnati , Vincent Fortuin

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…

Signal Processing · Electrical Eng. & Systems 2022-10-13 Muhammad Shoaib Farooq , Aimen Zulfiqar , Shamyla Riaz

The timeliness of detection of a sepsis event in progress is a crucial factor in the outcome for the patient. Machine learning models built from data in electronic health records can be used as an effective tool for improving this…

Background Sepsis is one of the most life-threatening circumstances for critically ill patients in the US, while a standardized criteria for sepsis identification is still under development. Disparities in social determinants of sepsis…

Machine Learning · Computer Science 2021-12-16 Hanyin Wang , Yikuan Li , Andrew Naidech , Yuan Luo

We applied machine learning to the unmet medical need of rapid and accurate diagnosis and prognosis of acute infections and sepsis in emergency departments. Our solution consists of a Myrna (TM) Instrument and embedded TriVerity (TM)…

Despite decades of clinical research, sepsis remains a global public health crisis with high mortality, and morbidity. Currently, when sepsis is detected and the underlying pathogen is identified, organ damage may have already progressed to…

Sepsis is a life-threatening host response to infection associated with high mortality, morbidity, and health costs. Its management is highly time-sensitive since each hour of delayed treatment increases mortality due to irreversible organ…

Machine Learning · Computer Science 2020-10-16 Michael Moor , Max Horn , Bastian Rieck , Damian Roqueiro , Karsten Borgwardt

Sepsis is an important cause of mortality, especially in intensive care unit (ICU) patients. Developing novel methods to identify early mortality is critical for improving survival outcomes in sepsis patients. Using the MIMIC-III database,…

Computers and Society · Computer Science 2021-12-03 Jiyoung Shin , Yikuan Li , Yuan Luo

Sepsis is a life threatening medical condition that occurs when the body has an extreme response to infection, leading to widespread inflammation, organ failure, and potentially death. Because sepsis can worsen rapidly, early detection is…

Machine Learning · Computer Science 2025-05-07 Oyindolapo O. Komolafe , Zhimin Mei , David Morales Zarate , Gregory William Spangenberg

Automated recognition and classification of bacteria species from microscopic images have significant importance in clinical microbiology. Bacteria classification is usually carried out manually by biologists using different shapes and…

Quantitative Methods · Quantitative Biology 2019-12-19 Muhammed Talo
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