AIMC Topic: Colorectal Neoplasms

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Towards the development of a FAIR-compliant biomedical ontology for colorectal cancer.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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...

Establishing and clinically validating a machine learning model for predicting unplanned reoperation risk in colorectal cancer.

World journal of gastroenterology
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...

Personalized prediction of survival rate with combination of penalized Cox models in patients with colorectal cancer.

Medicine
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...

Integrating artificial intelligence techniques for advancements in colorectal cancer management: navigating past and predicting future direction.

JPMA. The Journal of the Pakistan Medical Association
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...

Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

Cancer medicine
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...

Use of artificial intelligence for the prediction of lymph node metastases in early-stage colorectal cancer: systematic review.

BJS open
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...

[Research progress and prospects of artificial intelligence in diagnosis and treatment of colorectal cancer].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
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...

A comparative study of supervised and unsupervised machine learning algorithms applied to human microbiome.

La Clinica terapeutica
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...

Synthetic Data Improve Survival Status Prediction Models in Early-Onset Colorectal Cancer.

JCO clinical cancer informatics
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...

End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study.

The Lancet. Digital health
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...