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Related papers: Prediction of Delirium Risk in Mild Cognitive Impa…

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Delirium is a common acute onset brain dysfunction in the emergency setting and is associated with higher mortality. It is difficult to detect and monitor since its presentations and risk factors can be different depending on the underlying…

Machine Learning · Computer Science 2021-11-02 Yiqing Zhao , Yuan Luo

Although prediction models for delirium, a commonly occurring condition during general hospitalization or post-surgery, have not gained huge popularity, their algorithmic bias evaluation is crucial due to the existing association between…

Machine Learning · Computer Science 2022-11-29 Sandhya Tripathi , Bradley A Fritz , Michael S Avidan , Yixin Chen , Christopher R King

Elderly ICU patients with coexisting diabetes mellitus and heart failure experience markedly elevated short-term mortality, yet few predictive models are tailored to this high-risk group. Diabetes mellitus affects nearly 30% of U.S. adults…

Applications · Statistics 2025-06-19 Junyi Fan , Shuheng Chen , Li Sun , Yong Si , Elham Pishgar , Kamiar Alaei , Greg Placencia , Maryam Pishgar

Purpose: Summarize ICU delirium prediction models published within the past five years. Methods: Electronic searches were conducted in April 2019 using PubMed, Embase, Cochrane Central, Web of Science, and CINAHL to identify peer reviewed…

Introduction: It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia. Methods: A deep learning method is…

Computer Vision and Pattern Recognition · Computer Science 2019-04-17 Hongming Li , Mohamad Habes , David A. Wolk , Yong Fan

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…

Acute brain dysfunction (ABD) is a common, severe ICU complication, presenting as delirium or coma and leading to prolonged stays, increased mortality, and cognitive decline. Traditional screening tools like the Glasgow Coma Scale (GCS),…

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…

Coronary artery disease remains one of the leading causes of mortality globally. Despite advances in revascularization treatments like PCI and CABG, postoperative stroke is inevitable. This study aims to develop and evaluate a sophisticated…

Machine Learning · Computer Science 2025-03-18 Haonan Pan , Shuheng Chen , Elham Pishgar , Kamiar Alaei , Greg Placencia , Maryam Pishgar

Delirium occurs in about 80% cases in the Intensive Care Unit (ICU) and is associated with a longer hospital stay, increased mortality and other related issues. Delirium does not have any biomarker-based diagnosis and is commonly treated…

Machine Learning · Computer Science 2022-05-03 Riddhiman Adib , Md Osman Gani , Sheikh Iqbal Ahamed , Mohammad Adibuzzaman

Heart disease remains the leading cause of death in the United States. Compared with risk assessment guidelines that require manual calculation of scores, machine learning-based prediction for disease outcomes such as mortality can be…

Machine Learning · Computer Science 2018-12-13 Laura A. Barrett , Seyedeh Neelufar Payrovnaziri , Jiang Bian , Zhe He

Background: Patients with both diabetes mellitus (DM) and atrial fibrillation (AF) face elevated mortality in intensive care units (ICUs), yet models targeting this high-risk group remain limited. Objective: To develop an interpretable…

Machine Learning · Computer Science 2025-06-23 Li Sun , Shuheng Chen , Yong Si , Junyi Fan , Maryam Pishgar , Elham Pishgar , Kamiar Alaei , Greg Placencia

Purpose: This study investigates whether a machine-learning-based system can predict the rate of cognitive decline in mildly cognitively impaired patients by processing only the clinical and imaging data collected at the initial visit.…

Quantitative Methods · Quantitative Biology 2020-10-07 Sema Candemir , Xuan V. Nguyen , Luciano M. Prevedello , Matthew T. Bigelow , Richard D. White , Barbaros S. Erdal

Intensive care unit (ICU) is a crucial hospital department that handles life-threatening cases. Nowadays machine learning (ML) is being leveraged in healthcare ubiquitously. In recent years, management of ICU became one of the most…

Machine Learning · Computer Science 2025-05-26 Alexander Gabitashvili , Philipp Kellmeyer

Predicting the risk of clinical progression from cognitively normal (CN) status to mild cognitive impairment (MCI) or Alzheimer's disease (AD) is critical for early intervention in Alzheimer's disease (AD). Traditional survival models often…

Applications · Statistics 2025-03-24 Dhrubajyoti Ghosh , Samhita Pal , Michael Lutz , Sheng Luo

Traumatic Brain Injury (TBI) is a major contributor to mortality among older adults, with geriatric patients facing disproportionately high risk due to age-related physiological vulnerability and comorbidities. Early and accurate prediction…

Quantitative Methods · Quantitative Biology 2025-05-23 Yong Si , Junyi Fan , Li Sun , Shuheng Chen , Elham Pishgar , Kamiar Alaei , Greg Placencia , Maryam Pishgar

Background: Stroke is second-leading cause of disability and death among adults. Approximately 17 million people suffer from a stroke annually, with about 85% being ischemic strokes. Predicting mortality of ischemic stroke patients in…

Machine Learning · Computer Science 2024-09-04 Armin Abdollahi , Negin Ashrafi , Maryam Pishgar

Early identification of patients at risk for clinical deterioration in the intensive care unit (ICU) remains a critical challenge. Delayed recognition of impending adverse events, including mortality, vasopressor initiation, and mechanical…

Machine Learning · Computer Science 2026-03-17 Binesh Sadanandan

Objective Alzheimer disease (AD) is the most common cause of dementia, a syndrome characterized by cognitive impairment severe enough to interfere with activities of daily life. We aimed to conduct a systematic literature review (SLR) of…

Quantitative Methods · Quantitative Biology 2021-08-31 Sayantan Kumar , Inez Oh , Suzanne Schindler , Albert M Lai , Philip R O Payne , Aditi Gupta

Early detection of dementia is crucial to devise effective interventions. Comprehensive cognitive tests, while being the most accurate means of diagnosis, are long and tedious, thus limiting their applicability to a large population,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Anusha A. S. , Uma Ranjan , Medha Sharma , Siddharth Dutt
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