STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis

The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-temporal understanding capability of LLMs are somewhat limited and biased. These works either fail to incorporate the latest language models or only focus on assessing the memorized spatio-temporal knowledge. To address this gap, this paper dissects LLMs' capability of spatio-temporal data into four distinct dimensions: knowledge comprehension, spatio-temporal reasoning, accurate computation, and downstream applications. We curate several natural language question-answer tasks for each category and build the benchmark dataset, namely STBench, containing 13 distinct tasks and over 60,000 QA pairs. Moreover, we have assessed the capabilities of 13 LLMs, such as GPT-4o, Gemma and Mistral. Experimental results reveal that existing LLMs show remarkable performance on knowledge comprehension and spatio-temporal reasoning tasks, with potential for further enhancement on other tasks through in-context learning, chain-of-though prompting, and fine-tuning. The code and datasets of STBench are released on https://github.com/LwbXc/STBench

Ratio of metastatic to examined lymph nodes, a helpful staging system and independent prognostic factor of esophagogastric junction cancer.

BACKGROUND: The incidence of the esophagogastric junction cancer is growing rapidly. The purpose of this study is to clarify the outcome of the ratio between metastatic and examined lymph nodes in esophagogastric junction cancer patients with or without 7 examined lymph nodes. METHODS: A total of 3,481 patients who underwent operation are identified from the Surveillance, Epidemiology, and End Results database. Different lymph nodes resected groups are analyzed to test the lymph nodes ratio factor. RESULTS: There are 2522 patients with 7 or more lymph nodes resected and 959 patients with less than 7 lymph nodes resected. Lymph nodes ratio and lymph node involvement are independent prognostic factors. But the lymph nodes ratio categories have a better prognostic value than the lymph node involvement categories. Compared with lymph node involvement categories, lymph nodes ratio categories represent patients with more homogeneous overall survival rate. CONCLUSIONS: This study defines that the lymph nodes ratio is an independent prognostic factor for esophagogastric junction cancer. The lymph nodes ratio can prevent stage migration and may be a helpful system to predict the prognosis of esophagogastric junction cancer patients

D-dimer Can Be Used to Identify Vicious Phenotype in Gastric Cancer Patients With TNMⅠ-Ⅱ Stages: a Single Institution Experience Over 10 Years Study

Abstract BackgroundPart of gastric cancer (GC) patients in early stages still endure early relapse after systematic treatment. This study was designed to identify the value of d-dimer reflecting the bad phenotype in early GC patients. MethodsFrom January 1st 2009 to January 1st 2019, 467 primary GC patients with TNM stage I-II after R0 resection were enrolled, tumor stage was classified by the national comprehensive cancer network guideline 2019. Plasma D-dimer and associated factors were reviewed and analyzed with clinic-pathological characteristics, regularly follow up was proceed when first determined. ResultsThe median follow up is 33 months, and 381/467 GC patient survived after ten years follow up. Although D-dimer was significantly elevated in old age and vascular cancer emboli positive patients. Noteworthy, D-dimer levels displayed an increase in 48/467 GC patients when the cut-off values was 1.5 mg/ml based on the ROC curve in our previous study, log-rank and Cox hazard model analysis showed D-dimer is an independent risk factor for overall survival and disease free survival in this classification. ConclusionPlasma D-dimer represents an easy measurement and lower cost marker for the routine testing to predict highmalignancy phenotype in stage I-II gastric cancer after R0 resection.Clinical registrationChiCTR1900028178</jats:p