AIMC Topic: Colonic Neoplasms
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Establishment of a machine learning-based predictive model with dual-center external validation: investigating the role of robotic surgery in preventing delayed gastric emptying for right-sided colon cancer.
Journal of robotic surgery
Jun 30, 2025
After colorectal surgery, delayed gastric emptying (DGE) is a clinically significant postoperative complication that significantly lowers patients' quality of life. The evolving application of robotic surgery in gastrointestinal oncology continues to...
Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.
Techniques in coloproctology
Jun 11, 2025
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...
Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.
Nature communications
May 22, 2025
In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sectioning and staining remains a formidable challenge. We address this by integrating holotomography w...
Analyzing factors influencing hospitalization costs for five common cancers in China using neural network models.
Journal of medical economics
Apr 24, 2025
BACKGROUND: Malignant tumors are a major global health crisis, causing 25% of deaths in China, with lung, liver, thyroid, breast, and colon cancers being the most common. Understanding the factors influencing hospitalization costs for these cancers i...
A Novel Natural Language Processing Tool Improves Colonoscopy Auditing of Adenoma and Serrated Polyp Detection Rates.
Journal of gastroenterology and hepatology
Mar 31, 2025
BACKGROUND AND STUDY AIMS: Determining adenoma detection rate (ADR) and serrated polyp detection rate (SDR) can be challenging as they usually involve manual matching of colonoscopy and histology reports. This study aimed to validate a Natural Langua...
Aggregation induced emission luminogen bacteria hybrid bionic robot for multimodal phototheranostics and immunotherapy.
Nature communications
Mar 16, 2025
Multimodal phototheranostics utilizing single molecules offer a "one-and-done" approach, presenting a convenient and effective strategy for cancer therapy. However, therapies based on conventional photosensitizers often suffer from limitations such a...
Self-supervised learning reveals clinically relevant histomorphological patterns for therapeutic strategies in colon cancer.
Nature communications
Mar 8, 2025
Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-eosin-stained whole slide images (WSIs). We train an SSL Barlow Twins encoder on 435 colon adenocarcinoma WSIs from The C...
Do people prefer AI-generated patient educational materials over traditional ones?
Patient education and counseling
Jan 20, 2025
OBJECTIVE: This study aimed to assess people's preference between traditional and Artificial Intelligence (AI)-generated colon cancer staging Patient Education Materials (PEMs).
Analyzing Secondary Cancer Risk: A Machine Learning Approach.
Asian Pacific journal of cancer prevention : APJCP
Jan 1, 2025
OBJECTIVE: Addressing the rising cancer rates through timely diagnosis and treatment is crucial. Additionally, cancer survivors need to understand the potential risk of developing secondary cancer (SC), which can be influenced by several factors incl...
F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.
Asian Pacific journal of cancer prevention : APJCP
Jan 1, 2025
OBJECTIVE: This study aimed to develop a simple machine-learning model incorporating lymph node metastasis status with F-18 Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and clinical information for predicting regio...
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