Colon Cancer

Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer.

Tumor budding (TB), the presence of single cells or small clusters of up to 4 tumor cells at the invasive front of colorectal cancer (CRC), is a proven risk factor for adverse outcomes. International definitions are necessary to reduce interobserver variability. According to the current international guidelines, hotspots at the invasive front should be counted in hematoxylin and eosin (H&E)-staine...

Right hemicolectomy for ascending colon cancer using the hinotori surgical robot system: The first ever case report for colon cancer.

The hinotori Surgical Robot System obtained pharmaceutical approval for use in colorectal cancer surgery in October 2022 in Japan, and its advantages, including its operating arm with eight axes, adjustable arm base, and flexible 3D viewer, are expected to be utilized in colon cancer surgery. A 68-year-old woman presented to our hospital with abdominal pain and was diagnosed with cStageIIa (cT3N0M...

Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer.

Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR fro...

Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images.

In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of characterization and reporting on resected biopsies, incl...

Artificial intelligence in intestinal polyp and colorectal cancer prediction.

Artificial intelligence (AI) algorithms and their application to disease detection and decision support for healthcare professions have greatly evolve...

ChatGPT and Patient Questions About Colonoscopy: Comment.

Outcomes of robot-assisted versus laparoscopic surgery for colorectal cancer in morbidly obese patients: A propensity score-matched analysis of the US Nationwide Inpatient Sample.

BACKGROUND AND AIM: Morbid obesity is associated with poorer postoperative outcomes in colorectal cancer (CRC) patients. We aimed to evaluate short-te...

ChatGPT in Colorectal Surgery: A Promising Tool or a Passing Fad?

Colorectal surgery is a specialized branch of surgery that involves the diagnosis and treatment of conditions affecting the colon, rectum, and anus. I...

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging.

Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplastic lesions. This study aimed to develop a trial de...

An Investigation about Modern Deep Learning Strategies for Colon Carcinoma Grading.

Developing computer-aided approaches for cancer diagnosis and grading is currently receiving an increasing demand: this could take over intra- and int...

Dual-feature Fusion Attention Network for Small Object Segmentation.

Accurate segmentation of medical images is an important step during radiotherapy planning and clinical diagnosis. However, manually marking organ or l...

From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology.

While machine learning is currently transforming the field of histopathology, the domain lacks a comprehensive evaluation of state-of-the-art models b...

Preliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational status.

The detection of tumour gene mutations by DNA or RNA sequencing is crucial for the prescription of effective targeted therapies. Recent developments s...

XAI-enabled neural network analysis of metabolite spatial distributions.

We used deep neural networks to process the mass spectrometry imaging (MSI) data of mouse muscle (young vs aged) and human cancer (tumor vs normal adj...

Machine Learning Predicts the Oxidative Stress Subtypes Provide an Innovative Insight into Colorectal Cancer.

So far, it has been reached the academic consensus that the molecular subtypes are via genomic heterogeneity and immune infiltration patterns. Conside...

BCU-Net: Bridging ConvNeXt and U-Net for medical image segmentation.

Medical image segmentation enables doctors to observe lesion regions better and make accurate diagnostic decisions. Single-branch models such as U-Net...

Automated classification of polyps using deep learning architectures and few-shot learning.

BACKGROUND: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all...

Deep learning-based classification and spatial prognosis risk score on whole-slide images of lung adenocarcinoma.

AIMS: Classification of histological patterns in lung adenocarcinoma (LUAD) is critical for clinical decision-making, especially in the early stage. H...

Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms.

Cervical cancer is the most common reproductive malignancy in the female reproductive system. The incidence rate and mortality rate of cervical cancer...

Robotic colorectal resection in combination with a multimodal enhanced recovery program - results of the first 100 cases.

PURPOSE: In Germany, colorectal robot-assisted surgery (RAS) has found its way and is currently used as primary technique in colorectal resections at ...