{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T16:17:02Z","timestamp":1785428222419,"version":"3.56.0"},"reference-count":46,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62203130"],"award-info":[{"award-number":["62203130"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["62203130"],"award-info":[{"award-number":["62203130"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"crossref","award":["2024A1515011958"],"award-info":[{"award-number":["2024A1515011958"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biosensors"],"abstract":"<jats:p>Lymph node metastasis (LNM) is a key prognostic factor in esophageal squamous cell carcinoma (ESCC), and accurate preoperative prediction remains challenging. Blood biomarkers provide a conventional, preoperative diagnostic technique that is cost-effective and free from radiation risks. So far, previous studies have been published on the precise diagnosis of lymph node metastases using conventional ultrasound or CT techniques. While there is a lack of research studies that address the diagnosis of LNM from blood biomarkers. In this work, we acquired a cohort of blood biomarkers of 1933 patients and designed a weighted neural network (WNN) model for the accurate prediction of LNM from blood biomarkers. The WNN model is designed with a neural network classifier trained on blood biomarkers labeled with pathological nodal (pN) stages of LNM. The experimental findings demonstrate that the WNN model achieved 83.1% accuracy and an AUC of 0.88 on the original, non-augmented test set for diagnosing LNM, while CT only achieved 50.4% accuracy (AUC 0.60) and ultrasound achieved 60.5% accuracy (AUC 0.67). Additionally, SHAP analysis reveals that three blood biomarkers\u2014white blood cells (WBC#), monocytes (Mono#), and neutrophils (Neut#)\u2014significantly impact the WNN model\u2019s output. This WNN model shows promise as a research tool to diagnose LNM.<\/jats:p>","DOI":"10.3390\/bios16070377","type":"journal-article","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T09:46:47Z","timestamp":1783676807000},"page":"377","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Weighted Neural Network Model Based on Laboratory Tests for Identifying Lymph Node Metastases in Esophageal Squamous Cell Carcinomas"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9265-2660","authenticated-orcid":false,"given":"Qiangqiang","family":"Ouyang","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence and Low-Altitude Technology, South China Agricultural University, Guangzhou 510642, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziming","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Low-Altitude Technology, South China Agricultural University, Guangzhou 510642, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingbo","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Low-Altitude Technology, South China Agricultural University, Guangzhou 510642, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoyi","family":"Wang","sequence":"additional","affiliation":[{"name":"Ultrasound Department, Guangdong Provincial Occupational Disease Prevention Hospital, Guangzhou 510300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zonglin","family":"Li","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Low-Altitude Technology, South China Agricultural University, Guangzhou 510642, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Low-Altitude Technology, South China Agricultural University, Guangzhou 510642, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyou","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Low-Altitude Technology, South China Agricultural University, Guangzhou 510642, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinhua","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Oesophageal Cancer Research Institute, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runkun","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Oesophageal Cancer Research Institute, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7509-5820","authenticated-orcid":false,"given":"Hao","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Oesophageal Cancer Research Institute, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/S2468-1253(20)30007-8","article-title":"The global, regional, and national burden of oesophageal cancer and its attributable risk factors in 195 countries and territories, 1990\u20132017: A systematic analysis for the Global Burden of Disease Study 2017","volume":"5","author":"Kamangar","year":"2020","journal-title":"Lancet Gastroenterol. 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