Filtered By:
Specialty: Neurology
Education: Learning

This page shows you your search results in order of relevance. This is page number 6.

Order by Relevance | Date

Total 1309 results found since Jan 2013.

Measuring Functional Arm Movement after Stroke Using a Single Wrist-Worn Sensor and Machine Learning
We present a novel, inexpensive, and feasible method for separating UE functional use from nonfunctional movement after stroke using a single wrist-worn accelerometer.
Source: Journal of Stroke and Cerebrovascular Diseases - August 4, 2017 Category: Neurology Authors: Elaine M. Bochniewicz, Geoff Emmer, Adam McLeod, Jessica Barth, Alexander W. Dromerick, Peter Lum Source Type: research

Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke
The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatment from early stage of stroke.
Source: Journal of Stroke and Cerebrovascular Diseases - August 2, 2018 Category: Neurology Authors: Patrizio Sale, Giorgio Ferriero, Lucio Ciabattoni, Anna Maria Cortese, Francesco Ferracuti, Luca Romeo, Francesco Piccione, Stefano Masiero Source Type: research

Machine Learning for Brain Stroke: A Review
Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. An application of ML and Deep Learning in health care is growing however, some research areas do not catch enough attention for scientific investigation though there is real need of research. Therefore, the aim of this work is to classify state-of-arts on ML techniques for brain stroke into 4 categories based on their functionalities or similarity, and then review studies of each category systematically.
Source: Journal of Stroke and Cerebrovascular Diseases - August 11, 2020 Category: Neurology Authors: Manisha Sanjay Sirsat, Eduardo Ferm é, Joana Câmara Tags: Review Article Source Type: research

Reperfusion Therapy in Acute Ischemic Stroke with Active Cancer: A Meta-Analysis Aided by Machine Learning
While the prevalence of active cancer patients experiencing acute stroke is increasing, the effects of active cancer on reperfusion therapy outcomes are inconclusive. Thus, we aimed to compare the safety and outcomes of reperfusion therapy in acute stroke patients with and without active cancer.
Source: Journal of Stroke and Cerebrovascular Diseases - March 26, 2021 Category: Neurology Authors: Mi-Yeon Eun, Eun-Tae Jeon, Kwon-Duk Seo, Dongwhane Lee, Jin-Man Jung Source Type: research

Alberta Stroke Program Early CT Score Calculation Using the Deep Learning-Based Brain Hemisphere Comparison Algorithm
The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a promising tool for the evaluation of stroke expansion to determine suitability for reperfusion therapy. The aim of this study was to validate deep learning-based ASPECTS calculation software that utilizes a three-dimensional fully convolutional network-based brain hemisphere comparison algorithm (3D-BHCA).
Source: Journal of Stroke and Cerebrovascular Diseases - April 17, 2021 Category: Neurology Authors: Masaki Naganuma, Atsushi Tachibana, Takuya Fuchigami, Sadato Akahori, Shuichiro Okumura, Kenichiro Yi, Yoshimasa Matsuo, Koichi Ikeno, Toshiro Yonehara Source Type: research

Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge
This study aimed to identify the influential factors affecting home discharge in the stroke patients who use a wheelchair after discharge by using machine learning technology.
Source: Journal of Stroke and Cerebrovascular Diseases - May 21, 2021 Category: Neurology Authors: Takeshi Imura, Yuji Iwamoto, Yuki Azuma, Tetsuji Inagawa, Naoki Imada, Ryo Tanaka, Hayato Araki, Osamu Araki Source Type: research

Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke
Background Stratification of cardiovascular risk in patients with ischemic stroke is important as it may inform management strategies. We aimed to develop a machine-learning-derived prognostic model for the prediction of cardiovascular risk in ischemic stroke patients.
Source: Journal of Stroke and Cerebrovascular Diseases - August 2, 2021 Category: Neurology Authors: George Ntaios, Dimitrios Sagris, Athanasios Kallipolitis, Efstathia Karagkiozi, Eleni Korompoki, Efstathios Manios, Vasileios Plagianakos, Konstantinos Vemmos, Ilias Maglogiannis Source Type: research

Comparison of Supervised Machine Learning Algorithms for Classifying of Home Discharge Possibility in Convalescent Stroke Patients: A Secondary Analysis
Classifying the possibility of home discharge is important during stroke rehabilitation to support decision-making. There have been several studies on supervised machine learning algorithms, but only a few have compared the performance of different algorithms based on the same dataset for the classification of home discharge possibility. Therefore, we aimed to evaluate five supervised machine learning algorithms for the classification of home discharge possibility in stroke patients.
Source: Journal of Stroke and Cerebrovascular Diseases - July 26, 2021 Category: Neurology Authors: Takeshi Imura, Haruki Toda, Yuji Iwamoto, Tetsuji Inagawa, Naoki Imada, Ryo Tanaka, Yu Inoue, Hayato Araki, Osamu Araki Source Type: research

Clinical Prediction Rule for Identifying the Stroke Patients who will Obtain Clinically Important Improvement of Upper Limb Motor Function by Robot-Assisted Upper Limb
The number of studies on the characteristics of patients with stroke who would benefit from robot-assisted upper limb rehabilitation is limited, and there are no clear criteria for determining which individuals should receive such treatment. The current study aimed to develop a clinical prediction rule using machine learning to identify the characteristics of patients with stroke who can the achieve minimal clinically important difference of the Fugl-Meyer Upper Extremity Evaluation (FMA-UE) after single-joint hybrid assistive limb (HAL-SJ) rehabilitation.
Source: Journal of Stroke and Cerebrovascular Diseases - April 29, 2022 Category: Neurology Authors: Yuji Iwamoto, Takeshi Imura, Ryo Tanaka, Tsubasa Mitsutake, Hungu Jung, Takahiro Suzukawa, Shingo Taki, Naoki Imada, Tetsuji Inagawa, Hayato Araki, Osamu Araki Source Type: research

Collateral-Core Ratio as a Novel Predictor of Clinical Outcomes in Acute Ischemic Stroke
AbstractThe interaction effect between collateral circulation and ischemic core size on stroke outcomes has been highlighted in acute ischemic stroke (AIS). However, biomarkers that assess the magnitude of this interaction are still lacking. We aimed to present a new imaging marker, the collateral-core ratio (CCR), to quantify the interaction effect between these factors and evaluate its ability to predict functional outcomes using machine learning (ML) in AIS. Patients with AIS caused by anterior circulation large vessel occlusion (LVO) were recruited from a prospective multicenter study. CCR was calculated as collateral ...
Source: Translational Stroke Research - July 25, 2022 Category: Neurology Source Type: research

Direct Thrombin Inhibitor Argatroban Reduces Stroke Damage in 2 Different Models Brief Reports
Conclusions— We obtained supportive evidence for argatroban protection of the neurovascular unit using behavioral and histological measurements at realistic therapeutic time windows.
Source: Stroke - February 24, 2014 Category: Neurology Authors: Lyden, P., Pereira, B., Chen, B., Zhao, L., Lamb, J., Lei, I.-f., Rajput, P. Tags: Other anticoagulants, Other Treatment, Emergency treatment of Stroke, Other Vascular biology Brief Reports Source Type: research

Cognitive dysfunction after on-pump operations: neuropsychological characteristics and optimal core battery of tests.
Authors: Polunina AG, Golukhova EZ, Guekht AB, Lefterova NP, Bokeria LA Abstract Postoperative cognitive dysfunction (POCD) is a mild form of perioperative ischemic brain injury, which emerges as memory decline, decreased attention, and decreased concentration during several months, or even years, after surgery. Here we present results of our three neuropsychological studies, which overall included 145 patients after on-pump operations. We found that the auditory memory span test (digit span) was more effective as a tool for registration of POCD, in comparison with the word-list learning and story-learning tests. N...
Source: Stroke Research and Treatment - December 2, 2014 Category: Neurology Tags: Stroke Res Treat Source Type: research

Modification of the ladder rung walking task-new options for analysis of skilled movements.
Authors: Antonow-Schlorke I, Ehrhardt J, Knieling M Abstract Method sensitivity is critical for evaluation of poststroke motor function. Skilled walking was assessed in horizontal, upward, and downward rung ladder walking to compare the demands of the tasks and test sensitivity. The complete step sequence of a walk was subjected to analysis aimed at demonstrating the walking pattern, step sequence, step cycle, limb coordination, and limb interaction to complement the foot fault scoring system. Rats (males, n = 10) underwent unilateral photothrombotic lesion of the motor cortex of the forelimb and hind limb areas. L...
Source: Stroke Research and Treatment - December 2, 2014 Category: Neurology Tags: Stroke Res Treat Source Type: research

Automating Ischemic Stroke Subtype Classification Using Machine Learning and Natural Language Processing
This study sought to use natural language processing of electronic health records (EHR) combined with machine learning methods to automate IS subtyping. Methods: Among IS patients from an observational registry with TOAST subtyping adjudicated by board-certified vascular neurologists, we analyzed unstructured text-based EHR data including neurology progress notes and neuroradiology reports using natural language processing.
Source: Journal of Stroke and Cerebrovascular Diseases - May 14, 2019 Category: Neurology Authors: Ravi Garg, Elissa Oh, Andrew Naidech, Konrad Kording, Shyam Prabhakaran Source Type: research

Validity of quantitative assessment of posterior pelvic tilt and contralateral vaulting in hemiplegia using 3D treadmill gait analysis.
CONCLUSIONS: The proposed indices for posterior pelvic tilt and contralateral vaulting are useful for clinical gait analysis, and thus encouraging a more detailed analysis of hemiplegic gait using a motion analysis system. PMID: 32588758 [PubMed - as supplied by publisher]
Source: Topics in Stroke Rehabilitation - June 25, 2020 Category: Neurology Authors: Tanikawa H, Inagaki K, Ohtsuka K, Matsuda F, Mukaino M, Yamada J, Kanada Y, Kagaya H, Saitoh E Tags: Top Stroke Rehabil Source Type: research