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Total 2351 results found since Jan 2013.

Development and validation of a nomogram for predicting stroke risk in rheumatoid arthritis patients
In conclusion, the nomogram can be used for individualized preoperative prediction of stroke risk in RA patients.PMID:34081620 | DOI:10.18632/aging.203071
Source: Aging - June 3, 2021 Category: Biomedical Science Authors: Fangran Xin Lingyu Fu Bowen Yang Haina Liu Tingting Wei Cunlu Zou Bingqing Bai Source Type: research

Effect of the use of a body weight-supported walker on gait parameters in hemiplegic stroke patients
Conclusion] Using a BWS walker may help hemiplegic stroke patients learn to walk more efficiently in terms of their gait speed.PMID:34083884 | PMC:PMC8165362 | DOI:10.1589/jpts.33.434
Source: Physical Therapy - June 4, 2021 Category: Physiotherapy Authors: Hiroo Koshisaki Shota Nagai Source Type: research

Explicit motor sequence learning after stroke: a neuropsychological study
Exp Brain Res. 2021 Jun 5. doi: 10.1007/s00221-021-06141-5. Online ahead of print.ABSTRACTMotor learning interacts with and shapes experience-dependent cerebral plasticity. In stroke patients with paresis of the upper limb, motor recovery was proposed to reflect a process of re-learning the lost/impaired skill, which interacts with rehabilitation. However, to what extent stroke patients with hemiparesis may retain the ability of learning with their affected limb remains an unsolved issue, that was addressed by this study. Nineteen patients, with a cerebrovascular lesion affecting the right or the left hemisphere, underwent...
Source: Experimental Brain Research - June 6, 2021 Category: Neuroscience Authors: Cristina Russo Laura Veronelli Carlotta Casati Alessia Monti Laura Perucca Francesco Ferraro Massimo Corbo Giuseppe Vallar Nadia Bolognini Source Type: research

Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis
This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings.Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included.Results and ...
Source: Frontiers in Neurology - June 8, 2021 Category: Neurology Source Type: research

Tissue at Risk and Ischemic Core Estimation Using Deep Learning in Acute Stroke FUNCTIONAL
CONCLUSIONS: Deep learning models with fine-tuning lead to better performance for predicting tissue at risk and ischemic core, outperforming conventional thresholding methods.
Source: American Journal of Neuroradiology - June 10, 2021 Category: Radiology Authors: Yu, Y., Xie, Y., Thamm, T., Gong, E., Ouyang, J., Christensen, S., Marks, M. P., Lansberg, M. G., Albers, G. W., Zaharchuk, G. Tags: FUNCTIONAL Source Type: research

Immune-inflammatory, coagulation, adhesion, and imaging biomarkers combined in machine learning models improve the prediction of death 1  year after ischemic stroke
In conclusion, imaging, immune-inflammatory, and coagulation biomarkers add predictive information to the NIHSS clinical score and these biomarkers in combination may act as predictors of 1-year mortality after IS. An early prediction of IS outcome is important for personalized therapeutic strategies that may improve the outcome of IS.
Source: Clinical and Experimental Medicine - June 12, 2021 Category: Research Source Type: research

IJERPH, Vol. 18, Pages 6500: Free Fatty Acids Are Associated with the Cognitive Functions in Stroke Survivors
ta Szczuko Ischemic stroke is a leading cause of motor impairment and psychosocial disability. Although free fatty acids (FFA) have been proven to affect the risk of stroke and potentially dementia, the evidence of their impact on cognitive functions in stroke patients is lacking. We aimed to establish such potential relationships. Seventy-two ischemic stroke patients were prospectively analysed. Their cognitive functions were assessed seven days post-stroke and six months later as follow-up (n = 41). Seven days post-stroke analysis of serum FFAs levels showed direct correlations between Cognitive Verbal Learning Test ...
Source: International Journal of Environmental Research and Public Health - June 16, 2021 Category: Environmental Health Authors: Dariusz Kotl ęga Barbara Peda Joanna Palma Agnieszka Zembro ń-Łacny Monika Go łąb-Janowska Marta Masztalewicz Przemys ław Nowacki Ma łgorzata Szczuko Tags: Article Source Type: research

Prediction of Progression to Severe Stroke in Initially Diagnosed Anterior Circulation Ischemic Cerebral Infarction
Conclusion: The U-Net was fully automatic and showed a high correlation with manual segmentation. An integrated approach combining clinical variables and stroke lesion volumes that were derived from the advanced machine learning algorithms had high accuracy in predicting the progression to severe stroke in ASACNLII patients.
Source: Frontiers in Neurology - June 18, 2021 Category: Neurology Source Type: research

Impairment and Compensation in Dexterous Upper-Limb Function After Stroke. From the Direct Consequences of Pyramidal Tract Lesions to Behavioral Involvement of Both Upper-Limbs in Daily Activities
Impairments in dexterous upper limb function are a significant cause of disability following stroke. While the physiological basis of movement deficits consequent to a lesion in the pyramidal tract is well demonstrated, specific mechanisms contributing to optimal recovery are less apparent. Various upper limb interventions (motor learning methods, neurostimulation techniques, robotics, virtual reality, and serious games) are associated with improvements in motor performance, but many patients continue to experience significant limitations with object handling in everyday activities. Exactly how we go about consolidating ad...
Source: Frontiers in Human Neuroscience - June 21, 2021 Category: Neuroscience Source Type: research

Stroke care in Italy at the time of the COVID-19 pandemic: a lesson to learn
AbstractFrom March to May 2020, the Italian health care system, as many others, was almost entirely devoted to the fight against the COVID-19 pandemic. In this context, a number of questions arose, from the increased stroke risk due to COVID-19 infection to the quality of stroke patient care. The overwhelming need of COVID-19 patient management made mandatory a complete re-organization of the stroke pathways: many health professionals were reallocated and a number of stroke units was turned into COVID-19 wards. As a result, acute stroke care suffered from a shortage of services and delays in time-dependent treatments and d...
Source: Journal of Neurology - June 21, 2021 Category: Neurology Source Type: research

Sensors, Vol. 21, Pages 4269: Deep Learning-Based Stroke Disease Prediction System Using Real-Time Bio Signals
Jae-Hak Yu The emergence of an aging society is inevitable due to the continued increases in life expectancy and decreases in birth rate. These social changes require new smart healthcare services for use in daily life, and covid-19 has also led to a contactless trend necessitating more non-face-to-face health services. Due to the improvements that have been achieved in healthcare technologies, an increasing number of studies have attempted to predict and analyze certain diseases in advance. Research on stroke diseases is actively underway, particularly with the aging population. Stroke, which is fatal to the elderl...
Source: Sensors - June 22, 2021 Category: Biotechnology Authors: Yoon-A Choi Se-Jin Park Jong-Arm Jun Cheol-Sig Pyo Kang-Hee Cho Han-Sung Lee Jae-Hak Yu Tags: Article Source Type: research

A data-driven approach to post-stroke aphasia classification and lesion-based prediction
AbstractAphasia is an acquired impairment in the production or comprehension of language, typically caused by left hemisphere stroke. The subtyping framework used in clinical aphasiology today is based on the Wernicke-Lichtheim model of aphasia formulated in the late 19th century, which emphasizes the distinction between language production and comprehension. The current study used a data-driven approach that combined modern statistical, machine learning, and neuroimaging tools to examine behavioural deficit profiles and their lesion correlates and predictors in a large cohort of individuals with post-stroke aphasia. First...
Source: Brain - May 27, 2021 Category: Neurology Source Type: research

Exoskeleton-assisted Anthropomorphic Movement Training (EAMT) for Post-stroke Upper Limb Rehabilitation: A Pilot Randomized Controlled Trial
Stroke is the leading cause of mortality and disability worldwide, and it places a substantial burden on healthcare services and the socioeconomic system.1 More than two-thirds of individuals with stroke have upper extremity motor impairment and functional deficits at hospital admission,2, 3 manifesting as muscle weakness, loss of coordination and abnormal synergies.4 Moreover, upper limb dysfunction leads to long-term limitations in activities of daily living (ADL) and social participation.5 Extensive studies have reported that participants can benefit from high-intensity, task-specific training programs based on motor-le...
Source: Archives of Physical Medicine and Rehabilitation - June 23, 2021 Category: Rehabilitation Authors: Ze-Jian Chen, Chang He, Feng Guo, Cai-Hua Xiong, Xiao-Lin Huang Tags: Original Research Source Type: research

Quantification of Motor Function Post-Stroke Using Novel Combination of Wearable Inertial and Mechanomyographic Sensors
Subjective clinical rating scales represent the gold-standard for diagnosis of motor function following stroke. In practice however, they suffer from well-recognized limitations including assessor variance, low inter-rater reliability and low resolution. Automated systems have been proposed for empirical quantification but have not significantly impacted clinical practice. We address translational challenges in this arena through: (1) implementation of a novel sensor suite combining inertial measurement and mechanomyography (MMG) to quantify hand and wrist motor function; and (2) introduction of a new range of signal featu...
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - June 25, 2021 Category: Neuroscience Source Type: research

Sensors, Vol. 21, Pages 4482: NE-Motion: Visual Analysis of Stroke Patients Using Motion Sensor Networks
tavo Nonato A large number of stroke survivors suffer from a significant decrease in upper extremity (UE) function, requiring rehabilitation therapy to boost recovery of UE motion. Assessing the efficacy of treatment strategies is a challenging problem in this context, and is typically accomplished by observing the performance of patients during their execution of daily activities. A more detailed assessment of UE impairment can be undertaken with a clinical bedside test, the UE Fugl–Meyer Assessment, but it fails to examine compensatory movements of functioning body segments that are used to bypass impairment. In th...
Source: Sensors - June 30, 2021 Category: Biotechnology Authors: Rodrigo Colnago Contreras Avinash Parnandi Bruno Gomes Coelho Claudio Silva Heidi Schambra Luis Gustavo Nonato Tags: Article Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

MRI radiomic features-based machine learning approach to classify ischemic stroke onset time
ConclusionsA unique deep learning model based on DWI/ADC radiomic features was constructed for TSS classification, which could aid in decision making for thrombolysis in patients with unknown stroke onset.
Source: Journal of Neurology - July 4, 2021 Category: Neurology Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

SENSory re-learning of the UPPer limb (SENSUPP) after stroke: development and description of a novel intervention using the TIDieR checklist
Sensorimotor impairments of upper limb (UL) are common after stroke, leading to difficulty to use the UL in daily life. Even though many have sensory impairments in the UL, specific sensory training is often l...
Source: Trials - July 5, 2021 Category: General Medicine Authors: H åkan Carlsson, Birgitta Rosén, Anders Björkman, Hélène Pessah-Rasmussen and Christina Brogårdh Tags: Methodology Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Prediction of Motor Function in Stroke Patients Using Machine Learning Algorithm: Development of Practical Models
Machine learning (ML) techniques are being increasingly adopted in the medical field.
Source: Journal of Stroke and Cerebrovascular Diseases - May 19, 2021 Category: Neurology Authors: Jeoung Kun Kim, Yoo Jin Choo, Min Cheol Chang Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Prediction of 30-Day Readmission After Stroke Using Machine Learning and Natural Language Processing
Conclusion: NLP-enhanced machine learning models potentially advance our ability to predict readmission after stroke. However, further improvement is necessary before being implemented in clinical practice given the weak discrimination.
Source: Frontiers in Neurology - July 13, 2021 Category: Neurology Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

Predicting the Risk of Ischemic Stroke in Patients Treated with Novel Oral Anticoagulants: A Machine Learning Approach
Conclusions: The stroke risk in AF patients treated with NOAC could be predicted based on comorbidities like ischemic heart diseases, urinary tract infections, and dementia additionally to age and male sex. Knowing and addressing these factors may help reduce the risk of stroke in this patient population.Neuroepidemiology
Source: Neuroepidemiology - July 21, 2021 Category: Epidemiology Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

User engagement in the development of a home-based virtual multidisciplinary stroke care clinic for stroke survivors and caregivers: a qualitative descriptive study
CONCLUSION: This study provides findings of users' expectations of using telehealth services. Their perspectives on facilitators and barriers may increase the adoption of the newly developed telehealth service.Implications for rehabilitationTo implement telehealth as part of post-stroke care, it is important to ensure that stroke survivors and caregivers have the necessary information and communication technology support and infrastructure to engage in two-way interactions.Stroke survivors and caregivers may be inclined to use telehealth services due to ease of use, having flexibility in scheduling consultation sessions, d...
Source: Disability and Rehabilitation - July 23, 2021 Category: Rehabilitation Authors: Simon Kwun Yu Lam Janita Pak Chun Chau Suzanne Hoi Shan Lo Elaine Kee Chen Siow Vivian Wing Yan Lee Edward Wai Ching Shum Alexander Yuk Lun Lau Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

User engagement in the development of a home-based virtual multidisciplinary stroke care clinic for stroke survivors and caregivers: a qualitative descriptive study
CONCLUSION: This study provides findings of users' expectations of using telehealth services. Their perspectives on facilitators and barriers may increase the adoption of the newly developed telehealth service.Implications for rehabilitationTo implement telehealth as part of post-stroke care, it is important to ensure that stroke survivors and caregivers have the necessary information and communication technology support and infrastructure to engage in two-way interactions.Stroke survivors and caregivers may be inclined to use telehealth services due to ease of use, having flexibility in scheduling consultation sessions, d...
Source: Disability and Rehabilitation - July 23, 2021 Category: Rehabilitation Authors: Simon Kwun Yu Lam Janita Pak Chun Chau Suzanne Hoi Shan Lo Elaine Kee Chen Siow Vivian Wing Yan Lee Edward Wai Ching Shum Alexander Yuk Lun Lau Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research

Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke
CONCLUSIONS: In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.PMID:34198252 | DOI:10.3171/2021.4.FOCUS21134
Source: Neurosurgical Focus - July 1, 2021 Category: Neurosurgery Authors: Rania Abdelkhaleq Youngran Kim Swapnil Khose Peter Kan Sergio Salazar-Marioni Luca Giancardo Sunil A Sheth Source Type: research

Emerging role of artificial intelligence in stroke imaging
Expert Rev Neurother. 2021 Jul 20:1-10. doi: 10.1080/14737175.2021.1951234. Online ahead of print.ABSTRACTIntroduction: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clin...
Source: Expert Review of Neurotherapeutics - July 20, 2021 Category: Neurology Authors: Giuseppe Corrias Andrea Mazzotta Marta Melis Filippo Cademartiri Qi Yang Jasjit S Suri Luca Saba Source Type: research