{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T16:00:14Z","timestamp":1771257614743,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T00:00:00Z","timestamp":1681862400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Despite the growing interest in possible applications of computer science and artificial intelligence (AI) in the field of neurocritical care (neuro-ICU), widespread clinical applications are still missing. In neuro-ICU, the collection and analysis in real time of large datasets can play a crucial role in advancing this medical field and improving personalized patient care. For example, AI algorithms can detect subtle changes in brain activity or vital signs, alerting clinicians to potentially life-threatening conditions and facilitating rapid intervention. Consequently, data-driven AI and predictive analytics can greatly enhance medical decision making, diagnosis, and treatment, ultimately leading to better outcomes for patients. Nevertheless, there is a significant disparity between the current capabilities of AI systems and the potential benefits and applications that could be achieved with more advanced AI technologies. This gap is usually indicated as the AI chasm. In this paper, the underlying causes of the AI chasm in neuro-ICU are analyzed, along with proposed recommendations for utilizing AI to attain a competitive edge, foster innovation, and enhance patient outcomes. To bridge the AI divide in neurocritical care, it is crucial to foster collaboration among researchers, clinicians, and policymakers, with a focus on specific use cases. Additionally, strategic investments in AI technology, education and training, and infrastructure are needed to unlock the potential of AI technology. Before implementing a technology in patient care, it is essential to conduct thorough studies and establish clinical validation in real-world environments to ensure its effectiveness and safety. Finally, the development of ethical and regulatory frameworks is mandatory to ensure the secure and efficient deployment of AI technology throughout the process.<\/jats:p>","DOI":"10.3390\/computers12040083","type":"journal-article","created":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T03:25:11Z","timestamp":1681961111000},"page":"83","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Crossing the AI Chasm in Neurocritical Care"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5236-3132","authenticated-orcid":false,"given":"Marco","family":"Cascella","sequence":"first","affiliation":[{"name":"Pain Unit and Research, Istituto Nazionale Tumori IRCCS Fondazione Pascale, 80100 Napoli, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4028-9588","authenticated-orcid":false,"given":"Jonathan","family":"Montomoli","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, Infermi Hospital, AUSL Romagna, 47923 Rimini, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valentina","family":"Bellini","sequence":"additional","affiliation":[{"name":"Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2377-3765","authenticated-orcid":false,"given":"Alessandro","family":"Vittori","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Critical Care, ARCO ROMA, Ospedale Pediatrico Bambino Ges\u00f9, IRCCS, 00165 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2761-2552","authenticated-orcid":false,"given":"Helena","family":"Biancuzzi","sequence":"additional","affiliation":[{"name":"Department of Economics, Ca\u2019 Foscari University, 30121 Venice, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6477-4177","authenticated-orcid":false,"given":"Francesca","family":"Dal Mas","sequence":"additional","affiliation":[{"name":"Department of Management, Ca\u2019 Foscari University, 30121 Venice, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elena Giovanna","family":"Bignami","sequence":"additional","affiliation":[{"name":"Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"554633","DOI":"10.3389\/fneur.2020.554633","article-title":"Machine Learning Applications in the Neuro ICU: A Solution to Big Data Mayhem?","volume":"11","author":"Chaudhry","year":"2020","journal-title":"Front. 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