## 4 Discussion
The underlying mechanism by which B12 levels influence weight changes may involve processes related to lipid metabolism and alterations in the microbiome. The existing literature has also demonstrated that in B12-deficient adipocytes, cholesterol biosynthesis-related genes undergo hypomethyllation, leading to increased expression and cholesterol synthesis [32]. Furthermore, an observation that microbially produced B12 enhances liver lipid metabolism and reduces lipogenesis suggests a potential role for B12 in weight loss mechanisms [33]. This study also identified the superdiaphragmatic cross-section as a key region of interest (ROI) in abdominal CT imaging for predicting weight loss. Various intra-abdominal organs were examined as potential ROIs, including the liver, pancreas, and small intestine. However, the above-diaphragm-level cross-section consistently emerged as the most relevant ROI. This finding suggests that subcutaneous fat at this level plays a crucial role in predicting postoperative weight change. This result aligns with prior studies [34] that reported a lower CT radiodensity of abdominal subcutaneous fat in obese individuals compared to non-obese individuals. Additionally, these studies identified post-surgical changes in radiodensity as being associated with clinical outcomes. In addition, research on patients with liver cirrhosis [35] found that subcutaneous fat radiodensity was associated with mortality. Histological analysis revealed correlations between fat tissue characteristics and clinical outcomes, suggesting that similar mechanisms could potentially play a role in predicting postoperative weight loss in our study. This study has its limitations. First, while the identification of key variables--HOMA2-B, HOMA2-IR, insulin, and the above-diaphragm-level cross-section--was achieved, the determination of whether these factors have positive or negative effects on weight loss, as well as the quantification of their effect sizes, remains elusive. To further elucidate these relationships, additional research employing advanced interpretability techniques for deep learning models is imperative. Secondly, the development of the model was constrained by the utilization of data from 42 patients. To ensure the model's generalizability, future research should validate it across a more extensive and diverse patient population. Thirdly, this study used training and test sets from an internal source only. Employing external validation sets is expected to improve the performance and validity of WAD. Fourthly, while we hypothesized that subcutaneous fat located above the diaphragm level plays a role in weight loss, more precise segmentation of organs and anatomical structures through imaging analysis is needed to confirm this interpretation. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15052457/s1](https://www.mdpi.com/article/10.3390/app15052457/s1)]([https://www.mdpi.com/article/10.3390/app15052457/s1](https://www.mdpi.com/article/10.3390/app15052457/s1)), Table S1: Inclusion and exclusion criteria. [PERSON], [PERSON]-[PERSON] and Y.K. designed the study. [PERSON], K.-S.L. and Y.K. collected, analyzed, and interpreted the data. [PERSON], [PERSON], K.-S.L. and Y.K. wrote and reviewed the manuscript. [PERSON],[PERSON], K.-S.L. and Y.K. approved the final version of the manuscript. All authors have read and agreed to the published version of the manuscript. This work was supported by a grant of Korea University Anam Hospital (Seoul, Republic of Korea) (Y.K.) and the Korea Health Industry Development Institute grant (HI22C1302 (Korea Health Technology R&D Project)) funded by the Ministry of Health and Welfare of South Korea (K.-S.L.). The funder had no role in the design of the study, in the collection, analysis and interpretation of the data, or the writing and review of the manuscript. This retrospective study was approved by the Institutional Review Board of Korea University Anam Hospital on 17 August 2023 (2023 AN0364).