• Filter By:
• Specialty
• Source
• Condition
• Cancer
• Infectious Disease
• Drug
• Training
• Management
• Procedure
• Therapy
• Vaccine
• Nutrition
• Country

Sensors, Vol. 23, Pages 3500: A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform
il Roushdy Artificial intelligence (AI) techniques for intelligent mobile computing in healthcare has opened up new opportunities in healthcare systems. Combining AI techniques with the existing Internet of Medical Things (IoMT) will enhance the quality of care that patients receive at home remotely and the successful establishment of smart living environments. Building a real AI for mobile AI in an integrated smart hospital environment is a challenging problem due to the complexities of receiving IoT medical sensors data, data analysis, and deep learning algorithm complexity programming for mobile AI engine implementa...
Source: Sensors - March 27, 2023 Category: Biotechnology Authors: Bassant M. Elbagoury Luige Vladareanu Victor Vl ădăreanu Abdel Badeeh Salem Ana-Maria Travediu Mohamed Ismail Roushdy Tags: Article Source Type: research

Sensors, Vol. 22, Pages 9859: Explainable Artificial Intelligence Model for Stroke Prediction Using EEG Signal
This study aims to utilize ML models to classify the ischemic stroke group and the healthy control group for acute stroke prediction in active states. Moreover, XAI tools (Eli5 and LIME) were utilized to explain the behavior of the model and determine the significant features that contribute to stroke prediction models. In this work, we studied 48 patients admitted to a hospital with acute ischemic stroke and 75 healthy adults who had no history of identified other neurological illnesses. EEG was obtained within three months following the onset of ischemic stroke symptoms using frontal, central, temporal, and occipital cor...
Source: Sensors - December 15, 2022 Category: Biotechnology Authors: Mohammed Saidul Islam Iqram Hussain Md Mezbaur Rahman Se Jin Park Md Azam Hossain Tags: Article Source Type: research

Sensors, Vol. 21, Pages 7784: Detection of Unilateral Arm Paresis after Stroke by Wearable Accelerometers and Machine Learning
alle Åström Recent advances in stroke treatment have provided effective tools to successfully treat ischemic stroke, but still a majority of patients are not treated due to late arrival to hospital. With modern stroke treatment, earlier arrival would greatly improve the overall treatment results. This prospective study was performed to asses the capability of bilateral accelerometers worn in bracelets 24/7 to detect unilateral arm paralysis, a hallmark symptom of stroke, early enough to receive treatment. Classical machine learning algorithms as well as state-of-the-art deep neural networks were evaluated on detectio...
Source: Sensors - November 23, 2021 Category: Biotechnology Authors: Johan Wasselius Eric Lyckeg ård Finn Emma Persson Petter Ericson Christina Brog årdh Arne G. Lindgren Teresa Ullberg Kalle Åström Tags: Article Source Type: research

Sensors, Vol. 21, Pages 5334: Prediction of Myoelectric Biomarkers in Post-Stroke Gait
This study aimed to evaluate the potential myoelectric biomarkers for the classification of stroke-impaired muscular activity of the stroke patient group and the muscular activity of the control healthy adult group. We also proposed an EMG-based gait monitoring system consisting of a portable EMG device, cloud-based data processing, data analytics, and a health advisor service. This system was investigated with 48 stroke patients (mean age 70.6 years, 65% male) admitted into the emergency unit of a hospital and 75 healthy elderly volunteers (mean age 76.3 years, 32% male). EMG was recorded during walking using the portable...
Source: Sensors - August 7, 2021 Category: Biotechnology Authors: Iqram Hussain Se-Jin Park Tags: Article Source Type: research