Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Despite the widespread development of ontologies in many domains of healthcare, the field of colorectal cancer (CRC) presents a notable gap considering the lack of standardized data models tailored to the CRC domain. To address this gap, we developed...
BACKGROUND: Colorectal cancer significantly impacts global health, with unplanned reoperations post-surgery being key determinants of patient outcomes. Existing predictive models for these reoperations lack precision in integrating complex clinical d...
The investigation into individual survival rates within the patient population was typically conducted using the Cox proportional hazards model. This study was aimed to evaluate the performance of machine learning algorithm in predicting survival rat...
JPMA. The Journal of the Pakistan Medical Association
Apr 1, 2024
Artificial Intelligence (AI) in the last few years has emerged as a valuable tool in managing colorectal cancer, revolutionizing its management at different stages. In early detection and diagnosis, AI leverages its prowess in imaging analysis, scrut...
OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hematoxylin-Eosin (HE) slides and pathological immunohistochemistry (Ki67) slides for predicting the pa...
BACKGROUND: Risk evaluation of lymph node metastasis for early-stage (T1 and T2) colorectal cancers is critical for determining therapeutic strategies. Traditional methods of lymph node metastasis prediction have limited accuracy. This systematic rev...
Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
Jan 25, 2024
Colorectal cancer is one of the most common malignant tumors worldwide. Due to the heterogeneity in patient outcomes and treatment responses to standard therapy regimens, personalized diagnostic and therapeutic strategies have remained a focus of sus...
BACKGROUND: The human microbiome, consisting of diverse bacte-rial, fungal, protozoan and viral species, exerts a profound influence on various physiological processes and disease susceptibility. However, the complexity of microbiome data has present...
PURPOSE: In artificial intelligence-based modeling, working with a limited number of patient groups is challenging. This retrospective study aimed to evaluate whether applying synthetic data generation methods to the clinical data of small patient gr...
BACKGROUND: Precise prognosis prediction in patients with colorectal cancer (ie, forecasting survival) is pivotal for individualised treatment and care. Histopathological tissue slides of colorectal cancer specimens contain rich prognostically releva...
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