{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T12:05:43Z","timestamp":1790251543705,"version":"4.1.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eat Weight Disord"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Eating disorders (EDs), including anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED), are complex psychiatric conditions with high morbidity and mortality. Neuroimaging and machine learning (ML) represent promising approaches to improve diagnosis, understand pathophysiological mechanisms, and predict treatment response. This systematic review aimed to evaluate the application of ML techniques to neuroimaging data in EDs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Following PRISMA guidelines (PROSPERO registration: CRD42024628157), we systematically searched PubMed and APA PsycINFO for studies published between 2014 and 2024. Inclusion criteria encompassed human studies using neuroimaging and ML methods applied to AN, BN, or BED. Data extraction focused on study design, imaging modalities, ML techniques, and performance metrics. Quality was assessed using the GRADE framework and the ROBINS-I tool.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Out of 185 records screened, 5 studies met the inclusion criteria. Most applied support vector machines (SVMs) or other supervised ML models to structural MRI or diffusion tensor imaging data. Cortical thickness alterations in AN and diffusion-based metrics effectively distinguished ED subtypes. However, all studies were observational, heterogeneous, and at moderate to serious risk of bias. Sample sizes were small, and external validation was lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ML applied to neuroimaging shows potential for improving ED characterization and outcome prediction. Nevertheless, methodological limitations restrict generalizability. Future research should focus on larger, multicenter, and multimodal studies to enhance clinical applicability.<\/jats:p>\n                    <jats:p>\n                      <jats:italic>Level of Evidence<\/jats:italic>\n                      : Level IV, multiple observational studies with methodological heterogeneity and moderate to serious risk of bias.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s40519-025-01757-w","type":"journal-article","created":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T06:02:35Z","timestamp":1748757755000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Neuroimaging and machine learning in eating disorders: a systematic review"],"prefix":"10.1007","volume":"30","author":[{"given":"Francesco","family":"Monaco","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annarita","family":"Vignapiano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benedetta","family":"Di Gruttola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefania","family":"Landi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ernesta","family":"Panarello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raffaele","family":"Malvone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefania","family":"Palermo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandra","family":"Marenna","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrico","family":"Collantoni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanna","family":"Celia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valeria","family":"Di Stefano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Meneguzzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"D\u2019Angelo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulio","family":"Corrivetti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr.","given":"Luca","family":"Steardo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,1]]},"reference":[{"key":"1757_CR1","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2020-042685","author":"S Hamatani","year":"2021","unstructured":"Hamatani S, Hirano Y, Sugawara A et al (2021) Eating Disorder Neuroimaging Initiative (EDNI): a multicentre prospective cohort study protocol for elucidating the neural effects of cognitive-behavioural therapy for eating disorders. BMJ Open. https:\/\/doi.org\/10.1136\/bmjopen-2020-042685","journal-title":"BMJ Open"},{"key":"1757_CR2","doi-asserted-by":"publisher","DOI":"10.1055\/s-0042-1758859","author":"H Nagy","year":"2022","unstructured":"Nagy H, Paul T, Jain E, Loh H et al (2022) A clinical overview of anorexia nervosa and overcoming treatment resistance. Avicenna J Med. https:\/\/doi.org\/10.1055\/s-0042-1758859","journal-title":"Avicenna J Med"},{"key":"1757_CR3","doi-asserted-by":"publisher","first-page":"2594","DOI":"10.3390\/nu15112594","volume":"15","author":"VJ Clemente-Su\u00e1rez","year":"2023","unstructured":"Clemente-Su\u00e1rez VJ, Ram\u00edrez-Goerke MI, Redondo-Fl\u00f3rez L et al (2023) The impact of anorexia nervosa and the basis for non-pharmacological interventions. Nutrients 15:2594","journal-title":"Nutrients"},{"key":"1757_CR4","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1037\/0022-006X.76.2.329","volume":"76","author":"E Stice","year":"2008","unstructured":"Stice E, Marti CN, Spoor S et al (2008) Dissonance and healthy weight eating disorder prevention programs: long-term effects from a randomized efficacy trial. J Consult Clin Psychol 76:329\u2013340. https:\/\/doi.org\/10.1037\/0022-006X.76.2.329","journal-title":"J Consult Clin Psychol"},{"key":"1757_CR5","doi-asserted-by":"publisher","DOI":"10.1038\/s41572-022-00344-y","author":"KE Giel","year":"2022","unstructured":"Giel KE, Bulik CM, Fernandez-Aranda F et al (2022) Binge eating disorder. Nat Rev Dis Primers. https:\/\/doi.org\/10.1038\/s41572-022-00344-y","journal-title":"Nat Rev Dis Primers"},{"key":"1757_CR6","doi-asserted-by":"publisher","DOI":"10.1186\/s40337-022-00597-8","author":"E Bryant","year":"2022","unstructured":"Bryant E, Spielman K, Le A et al (2022) Screening, assessment and diagnosis in the eating disorders: findings from a rapid review. J Eat Disord. https:\/\/doi.org\/10.1186\/s40337-022-00597-8","journal-title":"J Eat Disord"},{"key":"1757_CR7","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1097\/YCO.0000000000000746","volume":"34","author":"LM Schaefer","year":"2021","unstructured":"Schaefer LM, Crosby RD, MacHado PPP (2021) A systematic review of instruments for the assessment of eating disorders among adults. Curr Opin Psychiatry 34:543\u2013562","journal-title":"Curr Opin Psychiatry"},{"key":"1757_CR8","doi-asserted-by":"publisher","first-page":"6325","DOI":"10.3390\/ijerph20146325","volume":"20","author":"B Feng","year":"2023","unstructured":"Feng B, Harms J, Chen E et al (2023) Current discoveries and future implications of eating disorders. Int J Environ Res Public Health 20:6325","journal-title":"Int J Environ Res Public Health"},{"key":"1757_CR9","doi-asserted-by":"publisher","DOI":"10.1186\/s40337-022-00717-4","author":"S Barakat","year":"2023","unstructured":"Barakat S, McLean SA, Bryant E et al (2023) Risk factors for eating disorders: findings from a rapid review. J Eat Disord. https:\/\/doi.org\/10.1186\/s40337-022-00717-4","journal-title":"J Eat Disord"},{"key":"1757_CR10","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1038\/s41593-022-01071-z","volume":"25","author":"CM Bulik","year":"2022","unstructured":"Bulik CM, Coleman JRI, Hardaway JA et al (2022) Genetics and neurobiology of eating disorders. Nat Neurosci 25:543\u2013554","journal-title":"Nat Neurosci"},{"key":"1757_CR11","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1016\/j.jpsychires.2022.10.058","volume":"156","author":"T Prince","year":"2022","unstructured":"Prince T, McLoughlin L, Lagopoulos J et al (2022) The neural correlates of socio-cognitive factors and eating disorders in young people: a systematic review. J Psychiatr Res 156:647\u2013659. https:\/\/doi.org\/10.1016\/j.jpsychires.2022.10.058","journal-title":"J Psychiatr Res"},{"key":"1757_CR12","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1002\/eat.22557","volume":"49","author":"MCT Slof-Opt Landt","year":"2016","unstructured":"Slof-Opt Landt MCT, Claes L, van Furth EF (2016) Classifying eating disorders based on \u201chealthy\u201d and \u201cunhealthy\u201d perfectionism and impulsivity. Int J Eat Disord 49:673\u201380. https:\/\/doi.org\/10.1002\/eat.22557","journal-title":"Int J Eat Disord"},{"key":"1757_CR13","doi-asserted-by":"publisher","first-page":"1108","DOI":"10.1002\/eat.23285","volume":"53","author":"K Soidla","year":"2020","unstructured":"Soidla K, Akkermann K (2020) Perfectionism and impulsivity based risk profiles in eating disorders. Int J Eat Disord 53:1108\u20131119. https:\/\/doi.org\/10.1002\/eat.23285","journal-title":"Int J Eat Disord"},{"key":"1757_CR14","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/s0193-953x(05)70221-5","volume":"24","author":"S Wonderlich","year":"2001","unstructured":"Wonderlich S, Mitchell JE (2001) The role of personality in the onset of eating disorders and treatment implications. Psychiatr Clin North Am 24:249\u2013258. https:\/\/doi.org\/10.1016\/s0193-953x(05)70221-5","journal-title":"Psychiatr Clin North Am"},{"key":"1757_CR15","doi-asserted-by":"publisher","first-page":"3343","DOI":"10.3390\/nu15153343","volume":"15","author":"M Abdoli","year":"2023","unstructured":"Abdoli M, Scotto Rosato M, Cipriano A et al (2023) Affect, body, and eating habits in children: a systematic review. Nutrients 15:3343","journal-title":"Nutrients"},{"key":"1757_CR16","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/7309878","author":"NA Al-Sheyab","year":"2018","unstructured":"Al-Sheyab NA, Gharaibeh T, Kheirallah K (2018) Relationship between peer pressure and risk of eating disorders among adolescents in Jordan. J Obes. https:\/\/doi.org\/10.1155\/2018\/7309878","journal-title":"J Obes"},{"key":"1757_CR17","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3390\/bs10040071","volume":"10","author":"M Erriu","year":"2020","unstructured":"Erriu M, Cimino S, Cerniglia L (2020) The role of family relationships in eating disorders in adolescents: a narrative review. Behav Sci 10:71","journal-title":"Behav Sci"},{"key":"1757_CR18","doi-asserted-by":"publisher","DOI":"10.1007\/s40519-024-01685-1","author":"J Chu","year":"2024","unstructured":"Chu J, Ganson KT, Testa A et al (2024) Screen time, problematic screen use, and eating disorder symptoms among early adolescents: findings from the Adolescent Brain Cognitive Development (ABCD) study. Eat Weight Disord. https:\/\/doi.org\/10.1007\/s40519-024-01685-1","journal-title":"Eat Weight Disord"},{"key":"1757_CR19","doi-asserted-by":"publisher","DOI":"10.3390\/nu15214687","author":"T Mushtaq","year":"2023","unstructured":"Mushtaq T, Ashraf S, Hameed H et al (2023) Prevalence of eating disorders and their association with social media addiction among youths. Nutrients. https:\/\/doi.org\/10.3390\/nu15214687","journal-title":"Nutrients"},{"key":"1757_CR20","doi-asserted-by":"publisher","unstructured":"Kappou K, Ntougia M, Kourtesi A et al (2021) children neuroimaging findings in adolescents and young adults with anorexia nervosa: a systematic review. https:\/\/doi.org\/10.3390\/children","DOI":"10.3390\/children"},{"key":"1757_CR21","doi-asserted-by":"publisher","DOI":"10.2147\/NDT.S25186","author":"I J\u00e1uregui-Lobera","year":"2011","unstructured":"J\u00e1uregui-Lobera I (2011) Neuroimaging in eating disorders. Neuropsychiatr Dis Treat. https:\/\/doi.org\/10.2147\/NDT.S25186","journal-title":"Neuropsychiatr Dis Treat"},{"key":"1757_CR22","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/s40337-018-0187-1","volume":"6","author":"B Donnelly","year":"2018","unstructured":"Donnelly B, Touyz S, Hay P et al (2018) Neuroimaging in bulimia nervosa and binge eating disorder: a systematic review. J Eat Disord 6:3. https:\/\/doi.org\/10.1186\/s40337-018-0187-1","journal-title":"J Eat Disord"},{"key":"1757_CR23","doi-asserted-by":"publisher","unstructured":"de Carvalho MNP, Dias MCF, Nogueira TDR et al (2024) Body image alterations in eating disorders patients: a systematic review of neuroimaging studies. https:\/\/doi.org\/10.21203\/rs.3.rs-4726800\/v1","DOI":"10.21203\/rs.3.rs-4726800\/v1"},{"key":"1757_CR24","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1186\/s12880-024-01432-z","volume":"24","author":"X Chen","year":"2024","unstructured":"Chen X, Ai C, Liu Z, Wang G (2024) Neuroimaging studies of resting-state functional magnetic resonance imaging in eating disorders. BMC Med Imaging 24:265","journal-title":"BMC Med Imaging"},{"key":"1757_CR25","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1002\/eat.22829","volume":"51","author":"GKW Frank","year":"2018","unstructured":"Frank GKW, Favaro A, Marsh R et al (2018) Toward valid and reliable brain imaging results in eating disorders. Int J Eat Disord 51:250\u2013261. https:\/\/doi.org\/10.1002\/eat.22829","journal-title":"Int J Eat Disord"},{"key":"1757_CR26","doi-asserted-by":"publisher","first-page":"E11","DOI":"10.1503\/jpn.230069","volume":"49","author":"Y Chen","year":"2024","unstructured":"Chen Y, Zhao P, Pan C et al (2024) State- and trait-related dysfunctions in bipolar disorder across different mood states: a graph theory study. J Psychiatry Neurosci 49:E11\u2013E22. https:\/\/doi.org\/10.1503\/jpn.230069","journal-title":"J Psychiatry Neurosci"},{"key":"1757_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2021.102671","author":"X Chen","year":"2021","unstructured":"Chen X, Gao X, Qin J et al (2021) Resting-state functional network connectivity underlying eating disorder symptoms in healthy young adults. Neuroimage Clin. https:\/\/doi.org\/10.1016\/j.nicl.2021.102671","journal-title":"Neuroimage Clin"},{"key":"1757_CR28","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.jpsychires.2023.05.059","volume":"161","author":"K Brack\u00e9","year":"2023","unstructured":"Brack\u00e9 K, Verschueren L, Geerardyn F et al (2023) The potential of neuroimaging results to predict the course of anorexia nervosa: a systematic review. J Psychiatr Res 161:34\u201347. https:\/\/doi.org\/10.1016\/j.jpsychires.2023.05.059","journal-title":"J Psychiatr Res"},{"key":"1757_CR29","doi-asserted-by":"publisher","DOI":"10.1186\/s40337-022-00581-2","author":"J Fardouly","year":"2022","unstructured":"Fardouly J, Crosby RD, Sukunesan S (2022) Potential benefits and limitations of machine learning in the field of eating disorders: current research and future directions. J Eat Disord. https:\/\/doi.org\/10.1186\/s40337-022-00581-2","journal-title":"J Eat Disord"},{"key":"1757_CR30","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1002\/hbm.24402","volume":"40","author":"AF Haynos","year":"2019","unstructured":"Haynos AF, Hall LMJ, Lavender JM et al (2019) Resting state functional connectivity of networks associated with reward and habit in anorexia nervosa. Hum Brain Mapp 40:652\u2013662. https:\/\/doi.org\/10.1002\/hbm.24402","journal-title":"Hum Brain Mapp"},{"key":"1757_CR31","doi-asserted-by":"publisher","first-page":"924814","DOI":"10.1155\/2015\/924814","volume":"2015","author":"A Cerasa","year":"2015","unstructured":"Cerasa A, Castiglioni I, Salvatore C et al (2015) Biomarkers of eating disorders using support vector machine analysis of structural neuroimaging data: preliminary results. Behav Neurol 2015:924814. https:\/\/doi.org\/10.1155\/2015\/924814","journal-title":"Behav Neurol"},{"key":"1757_CR32","doi-asserted-by":"publisher","first-page":"2805","DOI":"10.1017\/S0033291715000768","volume":"45","author":"L Lavagnino","year":"2015","unstructured":"Lavagnino L, Amianto F, Mwangi B et al (2015) Identifying neuroanatomical signatures of anorexia nervosa: a multivariate machine learning approach. Psychol Med 45:2805\u20132812. https:\/\/doi.org\/10.1017\/S0033291715000768","journal-title":"Psychol Med"},{"key":"1757_CR33","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1002\/eat.22828","volume":"51","author":"L Lavagnino","year":"2018","unstructured":"Lavagnino L, Mwangi B, Cao B et al (2018) Cortical thickness patterns as state biomarker of anorexia nervosa. Int J Eat Disord 51:241\u2013249. https:\/\/doi.org\/10.1002\/eat.22828","journal-title":"Int J Eat Disord"},{"key":"1757_CR34","doi-asserted-by":"publisher","first-page":"7827","DOI":"10.1017\/S0033291723001861","volume":"53","author":"D Arold","year":"2023","unstructured":"Arold D, Bernardoni F, Geisler D et al (2023) Predicting long-term outcome in anorexia nervosa: a machine learning analysis of brain structure at different stages of weight recovery. Psychol Med 53:7827\u20137836. https:\/\/doi.org\/10.1017\/S0033291723001861","journal-title":"Psychol Med"},{"key":"1757_CR35","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2023.1326271","author":"L Zheng","year":"2024","unstructured":"Zheng L, Wang Y, Ma J et al (2024) Machine learning research based on diffusion tensor images to distinguish between anorexia nervosa and bulimia nervosa. Front Psychiatry. https:\/\/doi.org\/10.3389\/fpsyt.2023.1326271","journal-title":"Front Psychiatry"},{"key":"1757_CR36","doi-asserted-by":"publisher","first-page":"1326271","DOI":"10.3389\/fpsyt.2023.1326271","volume":"14","author":"L Zhang","year":"2024","unstructured":"Zhang L, Wang Y, Ma J et al (2024) Machine learning research based on diffusion tensor images to distinguish between anorexia nervosa and bulimia nervosa. Front Psychiatry 14:1326271. https:\/\/doi.org\/10.3389\/fpsyt.2023.1326271","journal-title":"Frontiers in Psychiatry"},{"key":"1757_CR37","doi-asserted-by":"publisher","first-page":"E297","DOI":"10.15167\/2421-4248\/jpmh2022.63.2S3.2772","volume":"63","author":"K Donato","year":"2022","unstructured":"Donato K, Ceccarini MR, Dhuli K et al (2022) Gene variants in eating disorders. Focus on anorexia nervosa, bulimia nervosa, and binge-eating disorder. J Prev Med Hyg 63:E297\u2013E305. https:\/\/doi.org\/10.15167\/2421-4248\/jpmh2022.63.2S3.2772","journal-title":"J Prev Med Hyg"},{"key":"1757_CR38","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1002\/wps.21182","volume":"23","author":"M Solmi","year":"2024","unstructured":"Solmi M, Monaco F, H\u00f8jlund M et al (2024) Outcomes in people with eating disorders: a transdiagnostic and disorder-specific systematic review, meta-analysis and multivariable meta-regression analysis. World Psychiatry 23:124\u2013138. https:\/\/doi.org\/10.1002\/wps.21182","journal-title":"World Psychiatry"},{"key":"1757_CR39","doi-asserted-by":"publisher","first-page":"106994","DOI":"10.1016\/j.appet.2023.106994","volume":"189","author":"CE West","year":"2023","unstructured":"West CE, Hazzard VM, Loth KA et al (2023) The interplay between food insecurity and family factors in relation to disordered eating in adolescence. Appetite 189:106994. https:\/\/doi.org\/10.1016\/j.appet.2023.106994","journal-title":"Appetite"},{"key":"1757_CR40","doi-asserted-by":"publisher","first-page":"1174","DOI":"10.1038\/mp.2012.105","volume":"17","author":"S Kapur","year":"2012","unstructured":"Kapur S, Phillips AG, Insel TR (2012) Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Mol Psychiatry 17:1174\u20131179. https:\/\/doi.org\/10.1038\/mp.2012.105","journal-title":"Mol Psychiatry"},{"key":"1757_CR41","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1038\/mp.2011.182","volume":"17","author":"KS Kendler","year":"2012","unstructured":"Kendler KS (2012) The dappled nature of causes of psychiatric illness: replacing the organic\u2013functional\/hardware\u2013software dichotomy with empirically based pluralism. Mol Psychiatry 17:377\u2013388. https:\/\/doi.org\/10.1038\/mp.2011.182","journal-title":"Mol Psychiatry"},{"key":"1757_CR42","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1002\/eat.22835","volume":"51","author":"LR Vartanian","year":"2018","unstructured":"Vartanian LR, Hayward LE, Smyth JM et al (2018) Risk and resiliency factors related to body dissatisfaction and disordered eating: the identity disruption model. Int J Eat Disord 51:322\u2013330. https:\/\/doi.org\/10.1002\/eat.22835","journal-title":"Int J Eat Disord"},{"key":"1757_CR43","doi-asserted-by":"publisher","first-page":"1839","DOI":"10.1016\/j.neubiorev.2012.05.003","volume":"36","author":"S Gaudio","year":"2012","unstructured":"Gaudio S, Quattrocchi CC (2012) Neural basis of a multidimensional model of body image distortion in anorexia nervosa. Neurosci Biobehav Rev 36:1839\u20131847. https:\/\/doi.org\/10.1016\/j.neubiorev.2012.05.003","journal-title":"Neurosci Biobehav Rev"},{"key":"1757_CR44","doi-asserted-by":"publisher","first-page":"1414439","DOI":"10.3389\/fpsyt.2024.1414439","volume":"15","author":"F Monaco","year":"2024","unstructured":"Monaco F, Vignapiano A, Piacente M et al (2024) An advanced artificial intelligence platform for a personalised treatment of eating disorders. Front Psychiatry 15:1414439. https:\/\/doi.org\/10.3389\/fpsyt.2024.1414439","journal-title":"Front Psychiatry"},{"key":"1757_CR45","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1002\/hast.973","volume":"49","author":"AJ London","year":"2019","unstructured":"London AJ (2019) Artificial intelligence and black-box medical decisions: accuracy versus explainability. Hastings Cent Rep 49:15\u201321. https:\/\/doi.org\/10.1002\/hast.973","journal-title":"Hastings Cent Rep"},{"key":"1757_CR46","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1056\/NEJMp1714229","volume":"378","author":"DS Char","year":"2018","unstructured":"Char DS, Shah NH, Magnus D (2018) Implementing machine learning in health care \u2014 addressing ethical challenges. N Engl J Med 378:981\u2013983. https:\/\/doi.org\/10.1056\/NEJMp1714229","journal-title":"N Engl J Med"},{"key":"1757_CR47","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1353\/ppp.2021.0010","volume":"28","author":"M Maiese","year":"2021","unstructured":"Maiese M (2021) Anorexia nervosa, the visceral body, and the sense of ownership. Philos Psychiatry Psychol 28:63\u201365. https:\/\/doi.org\/10.1353\/ppp.2021.0010","journal-title":"Philos Psychiatry Psychol"},{"key":"1757_CR48","doi-asserted-by":"publisher","first-page":"e778","DOI":"10.1002\/mco2.778","volume":"5","author":"M-G Shi","year":"2024","unstructured":"Shi M-G, Feng X-M, Zhi H-Y et al (2024) Machine learning-based radiomics in neurodegenerative and cerebrovascular disease. MedComm 5:e778. https:\/\/doi.org\/10.1002\/mco2.778","journal-title":"MedComm"},{"key":"1757_CR49","doi-asserted-by":"publisher","DOI":"10.3390\/s24051572","author":"A Chudzik","year":"2024","unstructured":"Chudzik A, \u015aledzianowski A, Przybyszewski AW (2024) Machine learning and digital biomarkers can detect early stages of neurodegenerative diseases. Sensors. https:\/\/doi.org\/10.3390\/s24051572","journal-title":"Sensors"},{"key":"1757_CR50","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1001\/jamapsychiatry.2019.3671","volume":"77","author":"RA Poldrack","year":"2020","unstructured":"Poldrack RA, Huckins G, Varoquaux G (2020) Establishment of best practices for evidence for prediction. JAMA Psychiat 77:534. https:\/\/doi.org\/10.1001\/jamapsychiatry.2019.3671","journal-title":"JAMA Psychiat"}],"container-title":["Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40519-025-01757-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40519-025-01757-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40519-025-01757-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T06:02:36Z","timestamp":1748757756000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40519-025-01757-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,1]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1757"],"URL":"https:\/\/doi.org\/10.1007\/s40519-025-01757-w","relation":{},"ISSN":["1590-1262"],"issn-type":[{"value":"1590-1262","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,1]]},"assertion":[{"value":"27 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 June 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"46"}}