{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T01:31:03Z","timestamp":1769736663212,"version":"3.49.0"},"reference-count":54,"publisher":"FapUNIFESP (SciELO)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ala-Too International University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Braz. J. Biol."],"abstract":"<jats:p>Abstract Acute pancreatitis (AP) is a serious and potentially life-threatening condition characterized by a broad spectrum of disease severity, ranging from mild, self-limiting cases to severe, destructive forms associated with significant morbidity and mortality. Accurate prediction of clinical outcomes in AP is essential for timely intervention, effective resource allocation, and improved patient care. Recent advancements in artificial intelligence (AI) and machine learning (ML) have demonstrated significant potential in enhancing the accuracy of outcome prediction for acute pancreatitis. This article reviews the literature concerning the role of predictive models powered by artificial intelligence in acute pancreatitis (AP) focusing on their methods, evaluation criteria, and clinical usefulness. In addition, the review draws attention to data-related issues with the authors saying that the data is of insufficient quality, and the models cannot be properly explained, as well as other forms of bias in the algorithms used. Other ways are discussed, such as the use of real-time monitoring via wearable devices and the construction of explainable AI models, which shed light on the ways artificial intelligence is capable of changing the clinical approach to acute pancreatitis in the future.<\/jats:p>","DOI":"10.1590\/1519-6984.294105","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T15:05:33Z","timestamp":1760713533000},"source":"Crossref","is-referenced-by-count":1,"title":["Acute (destructive) pancreatitis: prediction of outcomes using artificial intelligence, a comprehensive review"],"prefix":"10.1590","volume":"85","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4469-1065","authenticated-orcid":false,"given":"K.","family":"Osmonaliev","sequence":"first","affiliation":[{"name":"Ala-Too International University,  Kyrgyzstan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5238-5211","authenticated-orcid":false,"given":"S. U.","family":"Rehman","sequence":"additional","affiliation":[{"name":"Ala-Too International University,  Kyrgyzstan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3623-2466","authenticated-orcid":false,"given":"E.","family":"Kudayarov","sequence":"additional","affiliation":[{"name":"Kyrgyz State Medical Academy,  Kyrgyzstan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0365-3405","authenticated-orcid":false,"given":"K.","family":"Aknazarov","sequence":"additional","affiliation":[{"name":"National Surgical Center,  Kyrgyzstan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2585-7292","authenticated-orcid":false,"given":"K.","family":"Sydygaliev","sequence":"additional","affiliation":[{"name":"Kyrgyz State Medical Academy,  Kyrgyzstan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8063-8351","authenticated-orcid":false,"given":"S.","family":"Aknazarov","sequence":"additional","affiliation":[{"name":"Ala-Too International University,  Kyrgyzstan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"530","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2024.1509362","article-title":"AI predicting recurrence in non-muscle-invasive bladder cancer: systematic review with study strengths and weaknesses","volume":"14","author":"ABBAS S.","year":"2025","journal-title":"Frontiers in Oncology"},{"key":"ref2","series-title":"AI-Powered Business Intelligence for Modern Organizations","first-page":"79","volume-title":"DDM: Data-Driven Marketing Using AI, ML, and Big Data","author":"AHAMED N.N.","year":"2025"},{"issue":"1","key":"ref3","doi-asserted-by":"crossref","first-page":"20","DOI":"10.14715\/cmb\/2025.70.1.3","article-title":"A critical evaluation of biochemical markers for the diagnosis of acute pancreatitis","volume":"71","author":"ALSHAHRANI M.M.","year":"2025","journal-title":"Cellular and Molecular Biology"},{"key":"ref4","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2024.102779","article-title":"Opportunities and challenges of artificial intelligence and distributed systems to improve the quality of healthcare service","volume":"149","author":"AMINIZADEH S.","year":"2024","journal-title":"Artificial Intelligence in Medicine"},{"issue":"3","key":"ref5","doi-asserted-by":"crossref","DOI":"10.1002\/ejp.4748","article-title":"Moving towards the use of artificial intelligence in pain management","volume":"29","author":"ANTEL R.","year":"2025","journal-title":"European Journal of Pain (London, England)"},{"issue":"1","key":"ref6","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1080\/21580103.2025.2456295","article-title":"Predictive modeling of volume and biomass in Pinus pseudostrobus using machine learning and allometric approaches","volume":"21","author":"ANT\u00daNEZ P.","year":"2025","journal-title":"Forest Science and Technology"},{"issue":"10","key":"ref7","article-title":"Revolutionizing radiology with artificial intelligence","volume":"16","author":"BHANDARI A.","year":"2024","journal-title":"Cureus"},{"issue":"1","key":"ref8","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1007\/s11916-024-01330-7","article-title":"Ethical considerations in the use of artificial intelligence in pain medicine","volume":"29","author":"CASCELLA M.","year":"2025","journal-title":"Current Pain and Headache Reports"},{"issue":"1","key":"ref9","doi-asserted-by":"crossref","DOI":"10.1016\/j.bj.2024.100743","article-title":"Applications of deep learning in trauma radiology: a narrative review","volume":"48","author":"CHENG C.T.","year":"2025","journal-title":"Biomedical Journal"},{"issue":"7","key":"ref10","article-title":"Diagnosing solid lesions in the pancreas with multimodal artificial intelligence: a randomized crossover trial","volume":"7","author":"CUI H.","year":"2024","journal-title":"JAMA Network Open"},{"key":"ref11","article-title":"A clinically actionable and explainable real-time risk assessment framework for stroke-associated pneumonia","volume":"149","author":"DAI L.","year":"2024","journal-title":"Artificial Intelligence in Medicine"},{"key":"ref12","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108880","article-title":"Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission","volume":"179","author":"EL-MENYAR A.","year":"2024","journal-title":"Computers in Biology and Medicine"},{"key":"ref13","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2024.102861","article-title":"Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations","volume":"151","author":"ESMAEILZADEH P.","year":"2024","journal-title":"Artificial Intelligence in Medicine"},{"issue":"6","key":"ref14","first-page":"58","article-title":"Transforming Healthcare with AI and Machine Learning: Revolutionizing Patient Care Through Advanced Analytics","volume":"11","author":"FATIMA S.","year":"2024","journal-title":"International Journal of Education and Science Research Review"},{"key":"ref15","series-title":"Ethical Dimensions of AI Development.","first-page":"23","volume-title":"Ethical Considerations in AI Development for Cloud Computing and Data-Driven Software Solutions.","author":"GADANI N.N.","year":"2025"},{"issue":"2","key":"ref16","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1136\/gutjnl-2023-331740","article-title":"Artificial intelligence applied to \u2018omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment","volume":"74","author":"GHOSH S.","year":"2025","journal-title":"Gut"},{"key":"ref17","series-title":"Revolutionizing AI with Brain-Inspired Technology: Neuromorphic Computing","first-page":"261","volume-title":"Classification of Moderate and Advanced Dementia Patients Using Gradient Boosting Machine Technique: Classification of Moderate and Advanced Dementia Patients","author":"GOWROJU S.","year":"2025"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s12262-024-04080-3","article-title":"Comparing and evaluating the role of early predictors like BISAP and Ranson Scoring System with Modified CT Severity Index in assessing the severity of acute pancreatitis","volume":"87","author":"GUPTA R.","year":"2024","journal-title":"Indian Journal of Surgery"},{"issue":"4","key":"ref19","doi-asserted-by":"crossref","DOI":"10.1016\/j.modpat.2025.100705","article-title":"Future of artificial intelligence - machine learning trends in pathology and medicine","volume":"38","author":"HANNA M.G.","year":"2025","journal-title":"Modern Pathology"},{"issue":"1","key":"ref20","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1007\/s13755-024-00331-5","article-title":"Real-time estimated Sequential Organ Failure Assessment (SOFA) score with intervals: improved risk monitoring with estimated uncertainty in health condition for patients in intensive care units","volume":"13","author":"HE Y.","year":"2025","journal-title":"Health Information Science and Systems"},{"key":"ref21","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2023.106649","article-title":"Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review","volume":"155","author":"HOSSAIN E.","year":"2023","journal-title":"Computers in Biology and Medicine"},{"issue":"37","key":"ref22","doi-asserted-by":"crossref","first-page":"5268","DOI":"10.3748\/wjg.v29.i37.5268","article-title":"Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence","volume":"29","author":"HU J.X.","year":"2023","journal-title":"World Journal of Gastroenterology"},{"issue":"1","key":"ref23","article-title":"Artificial intelligence\u2010driven change redefining radiology through interdisciplinary innovation","volume":"3","author":"HUANG R.","year":"2025","journal-title":"Interdisciplinary Medicine"},{"issue":"1","key":"ref24","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1053\/j.gastro.2021.09.043","article-title":"Global incidence of acute pancreatitis is increasing over time: a systematic review and meta-analysis","volume":"162","author":"IANNUZZI J.P.","year":"2022","journal-title":"Gastroenterology"},{"issue":"3","key":"ref25","doi-asserted-by":"crossref","DOI":"10.1148\/rg.240068","article-title":"Hepatobiliary and pancreatic neoplasms: essential predictive imaging features for personalized therapy","volume":"45","author":"IRIZATO M.","year":"2025","journal-title":"Radiographics"},{"key":"ref26","article-title":"Informatics strategies for early detection and risk mitigation in pancreatic cancer patients","volume":"60","author":"JIN D.","year":"2025","journal-title":"Neoplasia"},{"issue":"1","key":"ref27","first-page":"1465","article-title":"Leveraging machine learning for predictive models in healthcare to enhance patient outcome management","volume":"7","author":"KEHINDE A.O.","year":"2025","journal-title":"International Research Journal of Modernization in Engineering Technology and Science"},{"issue":"1","key":"ref28","first-page":"10","article-title":"A Framework for Automated Insights: Exploring AI-Driven Data Science Techniques","volume":"1","author":"KHAN M.","year":"2025","journal-title":"Intelligent Data Science and Analytics"},{"issue":"2","key":"ref29","doi-asserted-by":"crossref","first-page":"201","DOI":"10.5009\/gnl230272","article-title":"Challenges in and opportunities for electronic health record-based data analysis and interpretation","volume":"18","author":"KIM M.K.","year":"2024","journal-title":"Gut and Liver"},{"issue":"5","key":"ref30","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1002\/ncp.11194","article-title":"Role of artificial intelligence in critical care nutrition support and research","volume":"39","author":"KITTRELL H.D.","year":"2024","journal-title":"Nutrition in Clinical Practice"},{"key":"ref31","series-title":"AI in disease detection: advancements and applications","first-page":"53","volume-title":"Natural Language Processing (NLP) in disease detection \u2014 A discussion of how NLP Techniques can be used to analyze and classify medical text data for disease diagnosis","author":"KUMAR V.","year":"2025"},{"key":"ref32","article-title":"Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring","volume":"11","author":"LI F.","year":"2025","journal-title":"Frontiers in Medicine"},{"issue":"6","key":"ref33","doi-asserted-by":"crossref","first-page":"2336","DOI":"10.1111\/jocn.17660","article-title":"Development and validation of a prediction model for enteral feeding intolerance in critical ill patients: a retrospective cohort study","volume":"34","author":"LIU L.","year":"2025","journal-title":"Journal of Clinical Nursing"},{"key":"ref34","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102412","article-title":"Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework","volume":"108","author":"NASARIAN E.","year":"2024","journal-title":"Information Fusion"},{"issue":"1","key":"ref35","doi-asserted-by":"crossref","first-page":"32","DOI":"10.4103\/tjem.tjem_161_24","article-title":"Improved outcome prediction in acute pancreatitis with generated data and advanced machine learning algorithms","volume":"25","author":"\u00d6ZDEDE M.","year":"2025","journal-title":"Turkish Journal of Emergency Medicine"},{"issue":"8","key":"ref36","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1007\/s12032-022-01711-1","article-title":"Artificial intelligence and machine learning in precision and genomic medicine","volume":"39","author":"QUAZI S.","year":"2022","journal-title":"Medical Oncology"},{"key":"ref37","series-title":"Acute and chronic pancreatitis","first-page":"1","volume-title":"Emerging Innovations in the Management of Acute Pancreatitis","author":"RAM\u00cdREZ-MALDONADO E.","year":"2025"},{"issue":"2","key":"ref38","doi-asserted-by":"crossref","first-page":"50","DOI":"10.48185\/jaai.v5i2.1017","article-title":"Acceptance of artificial intelligence: key factors, challenges, and implementation strategies","volume":"5","author":"RANE N.","year":"2024","journal-title":"Journal of Applied Artificial Intelligence"},{"key":"ref39","doi-asserted-by":"crossref","DOI":"10.1016\/j.hybadv.2024.100277","article-title":"AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications","volume":"7","author":"RASHID A.B.","year":"2024","journal-title":"Hybrid Advances"},{"issue":"1","key":"ref40","doi-asserted-by":"crossref","first-page":"2899","DOI":"10.30574\/wjarr.2024.23.1.2255","article-title":"Decision-making in severe acute pancreatitis: the role of artificial intelligence and severity scales","volume":"23","author":"R\u00caGO A.C.M.","year":"2024","journal-title":"World Journal of Advanced Research and Reviews"},{"key":"ref41","first-page":"1759","article-title":"The Role of Artificial Intelligence in Genetic: Current and Future Perspective","volume":"25","author":"REHMAN S. U.","year":"2024","journal-title":"South Eastern European Journal of Public Health"},{"key":"ref42","doi-asserted-by":"crossref","DOI":"10.2196\/69007","article-title":"Era of generalist conversational artificial intelligence to support public health communications","volume":"27","author":"SEZGIN E.","year":"2025","journal-title":"Journal of Medical Internet Research"},{"key":"ref43","article-title":"Health is beyond genetics: on the integration of lifestyle and environment in real-time for hyper-personalized medicine","volume":"12","author":"TAN M.J.T.","year":"2025","journal-title":"Frontiers in Public Health"},{"issue":"1","key":"ref44","article-title":"Advancements in artificial intelligence in noninvasive cardiac imaging: a comprehensive review","volume":"48","author":"TOLU\u2010AKINNAWO O.Z.","year":"2025","journal-title":"Clinical Cardiology"},{"issue":"4","key":"ref45","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1053\/j.gastro.2024.02.052","article-title":"Diagnosis and management of acute pancreatitis","volume":"167","author":"TRIKUDANATHAN G.","year":"2024","journal-title":"Gastroenterology"},{"issue":"2","key":"ref46","doi-asserted-by":"crossref","first-page":"174","DOI":"10.3390\/diagnostics14020174","article-title":"From machine learning to patient outcomes: a comprehensive review of ai in pancreatic cancer","volume":"14","author":"TRIPATHI S.","year":"2024","journal-title":"Diagnostics"},{"issue":"4","key":"ref47","doi-asserted-by":"crossref","first-page":"1386","DOI":"10.51594\/estj.v5i4.1040","article-title":"AI\u2019s impact on personalized medicine: tailoring treatments for improved health outcomes","volume":"5","author":"UDEGBE F.C.","year":"2024","journal-title":"Engineering Science & Technology Journal"},{"key":"ref48","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126460","article-title":"Revolutionising industrial operations: the synergy of multiagent robotic systems and blockchain technology in operations planning and control","volume":"269","author":"VELASTEGUI R.","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"ref49","first-page":"1","article-title":"Prediction of severe acute pancreatitis at a very early stage of the disease using artificial intelligence techniques, without laboratory data or imaging tests: the PANCREATIA study","volume":"In press","author":"VILLASANTE S.","year":"2024","journal-title":"Annals of Surgery"},{"key":"ref50","first-page":"22883","author":"WANG C.","year":"2024"},{"issue":"1","key":"ref51","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1186\/s12877-024-05400-8","article-title":"The relationship between the Barthel Index and stroke-associated pneumonia in elderly patients and factors of SAP","volume":"24","author":"WU B.","year":"2024","journal-title":"BMC Geriatrics"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.csbj.2024.12.030","article-title":"AI-driven multi-omics integration for multi-scale predictive modeling of genotype-environment-phenotype relationships","volume":"27","author":"WU Y.","year":"2025","journal-title":"Computational and Structural Biotechnology Journal"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"41180","DOI":"10.1109\/ACCESS.2024.3376441","article-title":"A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends","volume":"12","author":"YOUNESI A.","year":"2024","journal-title":"IEEE Access"},{"issue":"1","key":"ref54","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1186\/s12880-024-01339-9","article-title":"A deep learning-powered diagnostic model for acute pancreatitis","volume":"24","author":"ZHANG C.","year":"2024","journal-title":"BMC Medical Imaging"}],"container-title":["Brazilian Journal of Biology"],"original-title":["Pancreatite aguda (destrutiva): predi\u00e7\u00e3o de resultados usando intelig\u00eancia artificial, uma revis\u00e3o abrangente"],"link":[{"URL":"http:\/\/www.scielo.br\/scielo.php?script=sci_pdf&pid=S1519-69842025000101008&tlng=en","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T15:06:06Z","timestamp":1760713566000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.scielo.br\/scielo.php?script=sci_arttext&pid=S1519-69842025000101008&tlng=en"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":54,"alternative-id":["S1519-69842025000101008"],"URL":"https:\/\/doi.org\/10.1590\/1519-6984.294105","relation":{},"ISSN":["1678-4375","1519-6984"],"issn-type":[{"value":"1678-4375","type":"electronic"},{"value":"1519-6984","type":"print"}],"subject":[],"published":{"date-parts":[[2025]]},"article-number":"e294105"}}