AIMC Topic: Colonic Neoplasms

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A machine learning-derived angiogenesis signature for clinical prognosis and immunotherapy guidance in colon adenocarcinoma.

Scientific reports
Colon adenocarcinoma (COAD) is one of the most prevalent malignancies worldwide and its prognosis is extremely poor. Angiogenesis has been linked to clinical outcomes, tumor progression, and treatment sensitivity. However, the role of angiogenesis in...

Evolutionary learning-derived lncRNA signature with biomarker discovery for predicting stage of colon adenocarcinoma.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In recent years, long non-coding RNAs (lncRNAs) have emerged as potential regulators of biological processes and genes, with the potential to serve as valuable biomarkers for cancer diagnosis and prognosis prediction. This work proposes an evolutiona...

Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence.

Cancer research communications
UNLABELLED: Deep learning may detect biologically important signals embedded in tumor morphologic features that confer distinct prognoses. Tumor morphologic features were quantified to enhance patient risk stratification within DNA mismatch repair (M...

Surgical stress response in robot-assisted versus laparoscopic surgery for colon cancer (SIRIRALS): randomized clinical trial.

The British journal of surgery
BACKGROUND: Evidence for the routine use of robotic technology and its impact on short-term outcomes in colon cancer surgery is lacking. The aim of this study was to compare the surgically induced systemic stress response and clinical and patient-rep...

A Hybrid 2D Gaussian Filter and Deep Learning Approach with Visualization of Class Activation for Automatic Lung and Colon Cancer Diagnosis.

Technology in cancer research & treatment
Cancer is a significant public health issue due to its high prevalence and lethality, particularly lung and colon cancers, which account for over a quarter of all cancer cases. This study aims to enhance the detection rate of lung and colon cancer by...

[Axillary Lymph Node Recurrence after Curative Surgery for Transverse Colon Cancer-A Case Report].

Gan to kagaku ryoho. Cancer & chemotherapy
We report the rare case of an 89-year-old female with axillary lymph node recurrence after curative surgery for transverse colon cancer who had undergone right hemicolectomy with D3 lymphadenectomy with an uneventful postoperative course. Pathologica...

Inteligencia artificial en la colonoscopia de tamizaje y la disminución del error.

Cirugia y cirujanos
Artificial Intelligence (AI) has the potential to change many aspects of healthcare practice. Image discrimination and classification has many applications within medicine. Machine learning algorithms and complicated neural networks have been develop...

Comparison of Robotic and Laparoscopic Colectomies Using the 2019 ACS NSQIP Database.

Southern medical journal
OBJECTIVES: Robot-assisted laparoscopic surgeries (RLSs) have become increasingly common in the past decade alongside conventional laparoscopic surgeries (CLSs). In general, RLSs have been reported to be superior to CLSs; therefore, we compared both ...

[Late anastomotic leakage in right-sided hemicolectomy with robot-assisted intracorporeal anastomosis technique].

Ugeskrift for laeger
A 65-year-old male with disseminated prostate cancer and newly diagnosed colonic cancer underwent elective robotic right hemicolectomy with intracorporeal anastomosis and had an uncomplicated short-term postoperative course. More than two years after...

HEAL: an automated deep learning framework for cancer histopathology image analysis.

Bioinformatics (Oxford, England)
MOTIVATION: Digital pathology supports analysis of histopathological images using deep learning methods at a large-scale. However, applications of deep learning in this area have been limited by the complexities of configuration of the computational ...