Novel Survival Features Generated by Clinical Text Information and Radiomics Features May Improve the Prediction of Ischemic Stroke Outcome

Article Clinical Neurology

MRI radiomic features-based machine learning approach to classify ischemic stroke onset time

Yi-Qun Zhang et al.

Summary: The study successfully classified the time since stroke onset using MRI radiomics features-based machine learning models, which could assist in stroke assessment and treatment decisions.

JOURNAL OF NEUROLOGY (2022)

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Article Environmental Sciences

Predictive Model and Mortality Risk Score during Admission for Ischaemic Stroke with Conservative Treatment

Maria Carmen Lea-Pereira et al.

Summary: This study aims to develop a predictive model to estimate the risk of mortality in stroke patients who have not received reperfusion treatment. The model, based on logistic regression and machine learning techniques, includes nine variables that are readily obtainable during initial care.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2022)

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Article Chemistry, Multidisciplinary

Evaluation of Post-Stroke Impairment in Fine Tactile Sensation by Electroencephalography (EEG)-Based Machine Learning

Jianing Zhang et al.

Summary: In this study, an EEG-based machine-learning model was established to automatically evaluate post-stroke impairments in fine tactile sensation. The model showed similar results to manual evaluation and may aid automatic assessments of post-stroke fine tactile sensations.

APPLIED SCIENCES-BASEL (2022)

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Article Medicine, General & Internal

Early COPD Risk Decision for Adults Aged From 40 to 79 Years Based on Lung Radiomics Features

Yingjian Yang et al.

Summary: This study evaluates the COPD risk for adults to make an early risk decision using lung radiomics features. The findings suggest that COPD patients need to take action to prevent disease progression and deterioration once they reach the age of 60. Precautions against COPD should be taken by patients with COPD stage 0 once they reach the age of 65.

FRONTIERS IN MEDICINE (2022)

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Article Mathematical & Computational Biology

A novel lung radiomics feature for characterizing resting heart rate and COPD stage evolution based on radiomics feature combination strategy

Yingjian Yang et al.

Summary: Resting heart rate increases with the development of chronic obstructive pulmonary disease (COPD) severity. Chest computed tomography (CT) provides more information to analyze the relationship between lung and heart. The relationship between resting heart rate variability and COPD radiomics features is not yet clear.

MATHEMATICAL BIOSCIENCES AND ENGINEERING (2022)

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Article Clinical Neurology

A Clinical-Radiomics Nomogram for Functional Outcome Predictions in Ischemic Stroke

Hao Wang et al.

Summary: This study developed and validated a radiomics nomogram for predicting ischemic stroke prognosis by combining clinical characteristics and radiomics features, showing good predictive performance and potential clinical value in assessing ischemic stroke outcomes.

NEUROLOGY AND THERAPY (2021)

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Article Multidisciplinary Sciences

Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models

Farideh Jalali-najafabadi et al.

Summary: The study focuses on developing feature selection and risk prediction models for psoriatic arthritis patients. Through the use of information theoretic criteria methods, the research demonstrates strategies for addressing potential confounding features in high-dimensional datasets.

SCIENTIFIC REPORTS (2021)

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Article Medicine, General & Internal

Prediction of Long-Term Stroke Recurrence Using Machine Learning Models

Vida Abedi et al.

Summary: Machine-learning models were trained to predict long-term stroke recurrence using patient-level data and interpretable algorithms, identifying important clinical features such as age, body mass index, and laboratory variables. Model performance could be optimized through different strategies to improve the balance between specificity and sensitivity.

JOURNAL OF CLINICAL MEDICINE (2021)

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Article Medicine, General & Internal

Machine-Learning-Based Rehabilitation Prognosis Prediction in Patients with Ischemic Stroke Using Brainstem Auditory Evoked Potential

Jangjay Sohn et al.

Summary: This study evaluated the feasibility of using BAEP for rehabilitation prognosis prediction in patients with ischemic stroke. The results suggest that combining BAEP interpeak latencies with the basal K-MBI score and age can assist in predicting patient rehabilitation prognoses.

DIAGNOSTICS (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Quantitative analysis of renal blood flow during thoracic endovascular aortic repair in type B aortic dissection using syngo iFlow

Kun Fang et al.

Summary: This study retrospectively analyzed 51 patients with type B aortic dissection undergoing thoracic endovascular aortic repair, quantitatively analyzing hemodynamic changes in renal artery blood flow and perfusion using novel realtime imaging software post stent graft placement. The results showed significant increases in avg.Pr and avg.AUCr, and a decrease in avg.dTTP after repair, with significant correlations between these parameters and renal function markers.

QUANTITATIVE IMAGING IN MEDICINE AND SURGERY (2021)

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Article Neuroimaging

An automatic machine learning approach for ischemic stroke onset time identification based on DWI and FLAIR imaging

Haichen Zhu et al.

Summary: The study proposes an automatic machine learning method for classifying TSS less than or more than 4.5 hours using DWI and FLAIR images. Experimental results demonstrate that the model accurately identifies TSS with high accuracy, sensitivity, and specificity, outperforming human reading DWI-FLAIR mismatch models.

NEUROIMAGE-CLINICAL (2021)

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Article Computer Science, Information Systems

Prediction of Stroke Lesion at 90-Day Follow-Up by Fusing Raw DSC-MRI With Parametric Maps Using Deep Learning

Adriano Pinto et al.

Summary: Stroke is the second most common cause of death in developed countries, and rapid clinical assessment and intervention play a crucial role in improving patients' quality of life. Clinical interventions aim to restore perfusion deficits, and a deep learning method can automatically predict ischemic stroke tissue outcome.

IEEE ACCESS (2021)

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Review Geriatrics & Gerontology

Radiomics in Stroke Neuroimaging: Techniques, Applications, and Challenges

Qian Chen et al.

Summary: Stroke is a major cause of disability and mortality globally, with neuroimaging playing a crucial role in guiding treatment decisions. Radiomics, a method of converting visual image information into quantitative features, has shown promise in stroke research for tasks such as diagnosis, prediction, and evaluation. Challenges remain in implementing radiomics in routine practice, but future research directions are being explored to further advance personalized precision medicine in stroke management.

AGING AND DISEASE (2021)

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Article Clinical Neurology

Penumbra-based radiomics signature as prognostic biomarkers for thrombolysis of acute ischemic stroke patients: a multicenter cohort study

Tian-yu Tang et al.

JOURNAL OF NEUROLOGY (2020)

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Article Clinical Neurology

Multimodal Predictive Modeling of Endovascular Treatment Outcome for Acute Ischemic Stroke Using Machine-Learning

Gianluca Brugnara et al.

STROKE (2020)

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Article Clinical Neurology

Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models

Shakiru A. Alaka et al.

FRONTIERS IN NEUROLOGY (2020)

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Article Medicine, General & Internal

Predicting Clinical Outcome in Acute Ischemic Stroke Using Parallel Multi-Parametric Feature Embedded Siamese Network

Saira Osama et al.

DIAGNOSTICS (2020)

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Article Engineering, Biomedical

Identification of the presence of ischaemic stroke lesions by means of texture analysis on brain magnetic resonance images

Rafael Ortiz-Ramon et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2019)

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Article Mathematical & Computational Biology

An Automatic Estimation of Arterial Input Function Based on Multi-Stream 3D CNN

Shengyu Fan et al.

FRONTIERS IN NEUROINFORMATICS (2019)

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Article Radiology, Nuclear Medicine & Medical Imaging

Machine-learning based classification of glioblastoma using delta-radiomic features derived from dynamic susceptibility contrast enhanced magnetic resonance images

Jiwoong Jeong et al.

QUANTITATIVE IMAGING IN MEDICINE AND SURGERY (2019)

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Article Radiology, Nuclear Medicine & Medical Imaging

Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information

Yuan Xie et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2019)

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Article Multidisciplinary Sciences

The impact of artificial intelligence in medicine on the future role of the physician

Abhimanyu S. Ahuja

PEERJ (2019)

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Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics features on non-contrast-enhanced CT scan can precisely classify AVM-related hematomas from other spontaneous intraparenchymal hematoma types

Yupeng Zhang et al.

EUROPEAN RADIOLOGY (2019)

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Article Clinical Neurology

Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke

Dorothea Pfeiffer et al.

STROKE (2019)

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Article Health Care Sciences & Services

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network

Jared L. Katzman et al.

BMC MEDICAL RESEARCH METHODOLOGY (2018)

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Review Clinical Neurology

Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches

M. Zhou et al.

AMERICAN JOURNAL OF NEURORADIOLOGY (2018)

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Review Oncology

Radiomics: the bridge between medical imaging and personalized medicine

Philippe Lambin et al.

NATURE REVIEWS CLINICAL ONCOLOGY (2017)

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Article Oncology

Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images

Janna E. van Timmeren et al.

RADIOTHERAPY AND ONCOLOGY (2017)

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Article Oncology

Computational Radiomics System to Decode the Radiographic Phenotype

Joost J. M. van Griethuysen et al.

CANCER RESEARCH (2017)

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Article Computer Science, Theory & Methods

Processor Design for Soft Errors: Challenges and State of the Art

Tuo Li et al.

ACM COMPUTING SURVEYS (2016)

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Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics: Images Are More than Pictures, They Are Data

Robert J. Gillies et al.

RADIOLOGY (2016)

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Article Medicine, General & Internal

A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke

O. A. Berkhemer et al.

NEW ENGLAND JOURNAL OF MEDICINE (2015)

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Article Neuroimaging

Admission neutrophil-lymphocyte ratio predicts 90 day outcome after endovascular stroke therapy

Steven D. Brooks et al.

JOURNAL OF NEUROINTERVENTIONAL SURGERY (2014)

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Article Emergency Medicine

Risk assessment of ischemic stroke associated pneumonia

Lin Li et al.

WORLD JOURNAL OF EMERGENCY MEDICINE (2014)

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Review Radiology, Nuclear Medicine & Medical Imaging

Quantitative Imaging in Cancer Evolution and Ecology

Robert A. Gatenby et al.

RADIOLOGY (2013)

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Article Clinical Neurology

RAPID Automated Patient Selection for Reperfusion Therapy A Pooled Analysis of the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET) and the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution (DEFUSE) Study

Maarten G. Lansberg et al.

STROKE (2011)

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Article Cardiac & Cardiovascular Systems

Assessment of neovascularization within carotid plaques in patients with ischemic stroke

Pin-Tong Huang et al.

WORLD JOURNAL OF CARDIOLOGY (2010)

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Article Clinical Neurology

Relationships Between Cerebral Perfusion and Reversibility of Acute Diffusion Lesions in DEFUSE Insights from RADAR

Jean-Marc Olivot et al.

STROKE (2009)

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Article Clinical Neurology

Change in Diffusion-Weighted Imaging Infarct Volume Predicts Neurologic Outcome at 90 Days Results of the Acute Stroke Accurate Prediction (ASAP) Trial Serial Imaging Substudy

Kevin M. Barrett et al.

STROKE (2009)

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Review Clinical Neurology

Epidemiology of Ischemic and Hemorrhagic Stroke: Incidence, Prevalence, Mortality, and Risk Factors

Rebbeca A. Grysiewicz et al.

NEUROLOGIC CLINICS (2008)

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Article Acoustics

Ultrasound perfusion imaging:: Determination of thresholds for the identification of critically disturbed perfusion in acute ischemic stroke -: A pilot study

Karsten Meyer-Wiethe et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2007)

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Article Clinical Neurology

Identification of penumbra and infarct in acute ischemic stroke using computed tomography perfusion-derived blood flow and blood volume measurements

B. D. Murphy et al.

STROKE (2006)

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Novel Survival Features Generated by Clinical Text Information and Radiomics Features May Improve the Prediction of Ischemic Stroke Outcome

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