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Predictive assessment of eating disorder risk and recovery: Uncovering the effectiveness of questionnaires and influencing characteristics
Predictive assessment of eating disorder risk and recovery: Uncovering the effectiveness of questionnaires and influencing characteristics

[u' @article{pikatza-huerga_predictive_2025, title = {Predictive assessment of eating disorder risk and recovery: {Uncovering} the effectiveness of questionnaires and influencing characteristics}, volume = {28}, issn = {20010370}, shorttitle = {Predictive assessment of eating disorder risk and recovery}, url = {https://linkinghub.elsevier.com/retrieve/pii/S2001037025001187}, doi = {10.1016/j.csbj.2025.03.048}, language = {en}, urldate = {2025-04-10}, journal = {Computational and Structural Biotechnology Journal}, author = {Pikatza-Huerga, A. and Las Hayas, C. and Zulaika, U. and Almeida, A.}, year = {2025}, keywords = {AI for health, eating disorders, feature importance, jcr, jcr4.5, machine learning, mental health, q1}, pages = {118--127}, } ']
Abstract