AIMC Topic: Colorectal Neoplasms

Clear Filters Showing 31 to 40 of 675 articles

T-cell receptor dynamics in digestive system cancers: a multi-layer machine learning approach for tumor diagnosis and staging.

Frontiers in immunology
BACKGROUND: T-cell receptor (TCR) repertoires provide insights into tumor immunology, yet their variations across digestive system cancers are not well understood. Characterizing TCR differences between colorectal cancer (CRC) and gastric cancer (GC)...

A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.

The Journal of pathology
Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichment of distinct T-cell subpopulations has been determined to impact the response to immune checkpoint ...

3D Hyperspectral Data Analysis with Spatially Aware Deep Learning for Diagnostic Applications.

Analytical chemistry
Nowadays, with the rise of artificial intelligence (AI), deep learning algorithms play an increasingly important role in various traditional fields of research. Recently, these algorithms have already spread into data analysis for Raman spectroscopy....

Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal of digestive diseases
OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.

Development and Multi-center validation of a machine learning Model for advanced colorectal neoplasms screening.

Computers in biology and medicine
BACKGROUND: In colorectal cancer (CRC) screening programs, accurately identifying individuals at high risk for advanced colorectal neoplasia (ACN) is essential as they require further colonoscopy, early intervention, and monitoring follow-up. This st...

Automated classification of tertiary lymphoid structures in colorectal cancer using TLS-PAT artificial intelligence tool.

Scientific reports
Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The immune system, particularly tertiary lymphoid structures (TLS), significantly influences CRC progression and prognosis. TLS maturation, especially in th...

A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation.

Scientific reports
Colorectal cancer (CRC) is a prevalent gastrointestinal tumor worldwide with high morbidity and mortality. Predicting the survival of CRC patients not only enhances understanding of their life expectancies but also aids clinicians in making informed ...

Utility of comprehensive genomic profiling combined with machine learning for prognostic stratification in stage II/III colorectal cancer after adjuvant chemotherapy.

International journal of clinical oncology
BACKGROUND AND PURPOSE: Accurate recurrence risk evaluation in patients with stage II and III colorectal cancer (CRC) remains difficult. Traditional histopathological methods frequently fall short in predicting outcomes after adjuvant chemotherapy. T...

Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers.

Annals of clinical and translational neurology
OBJECTIVE: Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk-prediction model incorpor...

A deep-learning model to predict the completeness of cytoreductive surgery in colorectal cancer with peritoneal metastasis☆.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Colorectal cancer (CRC) with peritoneal metastasis (PM) is associated with poor prognosis. The Peritoneal Cancer Index (PCI) is used to evaluate the extent of PM and to select Cytoreductive Surgery (CRS). However, PCI score is not accurat...