Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature
Introduction: In recent years, artificial intelligence (AI) has emerged as a transformative tool for enhancing stroke diagnosis, aiding treatment decision making, and improving overall patient care. Leading AI-driven platforms such as RapidAI, Brainomix<sup>®</sup>, and Viz.ai have been...
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2024-11-01
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| author | Omar M. Al-Janabi Amro El Refaei Tasnim Elgazzar Yamama M. Mahmood Danah Bakir Aryan Gajjar Aysha Alateya Saroj Kumar Jha Sherief Ghozy David F. Kallmes Waleed Brinjikji |
| author_facet | Omar M. Al-Janabi Amro El Refaei Tasnim Elgazzar Yamama M. Mahmood Danah Bakir Aryan Gajjar Aysha Alateya Saroj Kumar Jha Sherief Ghozy David F. Kallmes Waleed Brinjikji |
| author_sort | Omar M. Al-Janabi |
| collection | DOAJ |
| description | Introduction: In recent years, artificial intelligence (AI) has emerged as a transformative tool for enhancing stroke diagnosis, aiding treatment decision making, and improving overall patient care. Leading AI-driven platforms such as RapidAI, Brainomix<sup>®</sup>, and Viz.ai have been developed to assist healthcare professionals in the swift and accurate assessment of stroke patients. Methods: Following the PRISMA guidelines, a comprehensive systematic review was conducted using PubMed, Embase, Web of Science, and Scopus. Characteristic descriptive measures were gathered as appropriate from all included studies, including the sensitivity, specificity, accuracy, and comparison of the available tools. Results: A total of 31 studies were included, of which 29 studies focused on detecting acute ischemic stroke (AIS) or large vessel occlusions (LVOs), and 2 studies focused on hemorrhagic strokes. The four main tools used were Viz.ai, RapidAI, Brainomix<sup>®</sup>, and deep learning modules. Conclusions: AI tools in the treatment of stroke have demonstrated usefulness for diagnosing different stroke types, providing high levels of accuracy and helping to make quicker and more precise clinical judgments. |
| format | Article |
| id | doaj-art-b27af6166f0c41edbf862e9fbaee5c42 |
| institution | DOAJ |
| issn | 2076-3425 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj-art-b27af6166f0c41edbf862e9fbaee5c422025-08-20T02:53:38ZengMDPI AGBrain Sciences2076-34252024-11-011412118210.3390/brainsci14121182Current Stroke Solutions Using Artificial Intelligence: A Review of the LiteratureOmar M. Al-Janabi0Amro El Refaei1Tasnim Elgazzar2Yamama M. Mahmood3Danah Bakir4Aryan Gajjar5Aysha Alateya6Saroj Kumar Jha7Sherief Ghozy8David F. Kallmes9Waleed Brinjikji10Department of Neurology, Baptist Health, Lexington, KY 40503, USADepartment of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USACollege of Medicine, Alfaisal University, Riyadh 11533, Saudi ArabiaCentral Pharmacy, University of Kentucky Healthcare, Lexington, KY 40536, USADepartment of Neurology, School of Medicine, Southern Illinois University, Springfield, IL 62901, USADepartment of Radiological Sciences and Neurological Surgery, David Geffen School of Medicine, University of California, Los Angeles, CA 92093, USASchool of Medicine, Royal College of Surgeons in Ireland, Adliya P.O. Box 15503, BahrainTribhuvan University Teaching Hospital, Kathmandu 44600, NepalDepartments of Neurology and Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USADepartment of Radiology, Mayo Clinic, Rochester, MN 55905, USADepartment of Radiology, Mayo Clinic, Rochester, MN 55905, USAIntroduction: In recent years, artificial intelligence (AI) has emerged as a transformative tool for enhancing stroke diagnosis, aiding treatment decision making, and improving overall patient care. Leading AI-driven platforms such as RapidAI, Brainomix<sup>®</sup>, and Viz.ai have been developed to assist healthcare professionals in the swift and accurate assessment of stroke patients. Methods: Following the PRISMA guidelines, a comprehensive systematic review was conducted using PubMed, Embase, Web of Science, and Scopus. Characteristic descriptive measures were gathered as appropriate from all included studies, including the sensitivity, specificity, accuracy, and comparison of the available tools. Results: A total of 31 studies were included, of which 29 studies focused on detecting acute ischemic stroke (AIS) or large vessel occlusions (LVOs), and 2 studies focused on hemorrhagic strokes. The four main tools used were Viz.ai, RapidAI, Brainomix<sup>®</sup>, and deep learning modules. Conclusions: AI tools in the treatment of stroke have demonstrated usefulness for diagnosing different stroke types, providing high levels of accuracy and helping to make quicker and more precise clinical judgments.https://www.mdpi.com/2076-3425/14/12/1182acute ischemic strokehemorrhagic strokelarge vessel occlusionartificial intelligencedeep learningautomated detection |
| spellingShingle | Omar M. Al-Janabi Amro El Refaei Tasnim Elgazzar Yamama M. Mahmood Danah Bakir Aryan Gajjar Aysha Alateya Saroj Kumar Jha Sherief Ghozy David F. Kallmes Waleed Brinjikji Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature Brain Sciences acute ischemic stroke hemorrhagic stroke large vessel occlusion artificial intelligence deep learning automated detection |
| title | Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature |
| title_full | Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature |
| title_fullStr | Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature |
| title_full_unstemmed | Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature |
| title_short | Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature |
| title_sort | current stroke solutions using artificial intelligence a review of the literature |
| topic | acute ischemic stroke hemorrhagic stroke large vessel occlusion artificial intelligence deep learning automated detection |
| url | https://www.mdpi.com/2076-3425/14/12/1182 |
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