AIMC Topic: Colorectal Neoplasms

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Time-frequency time-space long short-term memory networks for image classification of histopathological tissue.

Scientific reports
Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultim...

Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.

Cancer research and treatment
PURPOSE: Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC...

Improved perioperative outcomes and reduced inflammatory stress response in malignant robot-assisted colorectal resections: a retrospective cohort study of 298 patients.

World journal of surgical oncology
BACKGROUND: Robot-assisted surgery is increasingly implemented for the resection of colorectal cancer, although the scientific evidence for adopting this technique is still limited. This study's main objective was to compare short-term complication r...

Intraoperative and postoperative complications in colorectal procedures: the role of continuous updating in medicine.

Minerva surgery
Accepting surgical complications, especially those related to the learning curve, as unavoidable events in colorectal procedures, is like accepting to fly onboard an aircraft with a 10% to 20% chance of not arriving at final destination. Under this c...

Histopathological characteristics and artificial intelligence for predicting tumor mutational burden-high colorectal cancer.

Journal of gastroenterology
BACKGROUND: Tumor mutational burden-high (TMB-H), which is detected with gene panel testing, is a promising biomarker for immune checkpoint inhibitors (ICIs) in colorectal cancer (CRC). However, in clinical practice, not every patient is tested for T...

Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.

International journal of cancer
High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer (CRC) and is an important predictive marker for response to immune checkpoint inhibitors. To test the feasibility of a deep learning (DL)-based classi...

Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in Wild-Type Metastatic Colorectal Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are associated with anti-EGFR agent response in metastatic colorectal cancer (mCRC). However, ligand RNA assays have not been adopted into routine practice ...

Detection of flat colorectal neoplasia by artificial intelligence: A systematic review.

Best practice & research. Clinical gastroenterology
OBJECTIVES: This study review focuses on a deep learning method for the detection of colorectal lesions in colonoscopy and AI support for detecting colorectal neoplasia, especially in flat lesions.