AIMC Topic: Adenocarcinoma
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Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.
Scientific reports
Dec 30, 2024
Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significant management implications. We assessed the performance of radiomics-based models in distinguishing ...
Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.
Scientific reports
Dec 30, 2024
Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as one of the most prevalent malignant tumors of the digestive tract, has been indicated by research to have a close association with CD. This study empl...
Machine learning-based prediction of duodenal stump leakage following laparoscopic gastrectomy for gastric cancer.
Surgery
Dec 27, 2024
BACKGROUND: Duodenal stump leakage is one of the most critical complications following gastrectomy surgery, with a high mortality rate. The present study aimed to establish a predictive model based on machine learning for forecasting the occurrence o...
Optimizing the management of immune-related adverse events and survival in patients with thoracic cancer receiving immunotherapy through artificial intelligence (electronic patient-reported outcomes): The IMPATHI study.
Bulletin du cancer
Dec 18, 2024
INTRODUCTION: The lung cancer continues to be the primary cause of cancer-related deaths, despite significant advancements in treatment through the introduction of immunological checkpoint inhibitors (ICI). These inhibitors, initially used as monothe...
Machine learning model for early prediction of survival in gallbladder adenocarcinoma: A comparison study.
SLAS technology
Nov 9, 2024
The prognosis for gallbladder adenocarcinoma (GBAC), a highly malignant cancer, is not good. In order to facilitate individualized risk stratification and improve clinical decision-making, this study set out to create and validate a machine learning ...
Weakly Supervised Multiple Instance Learning Model With Generalization Ability for Clinical Adenocarcinoma Screening on Serous Cavity Effusion Pathology.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Nov 6, 2024
Accurate and rapid screening of adenocarcinoma cells in serous cavity effusion is vital in diagnosing the stage of metastatic tumors and providing prompt medical treatment. However, it is often difficult for pathologists to screen serous cavity effus...
Machine learning and explainable artificial intelligence to predict pathologic stage in men with localized prostate cancer.
The Prostate
Oct 13, 2024
BACKGROUND: Though several nomograms exist, machine learning (ML) approaches might improve prediction of pathologic stage in patients with prostate cancer. To develop ML models to predict pathologic stage that outperform existing nomograms that use r...
Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators.
Frontiers in immunology
Sep 19, 2024
BACKGROUND: Moderately differentiated gastric adenocarcinoma (MDGA) has a high risk of metastasis and individual variation, which strongly affects patient prognosis. Using large-scale datasets and machine learning algorithms for prediction can improv...
Artificial Intelligence Recognition Model Using Liquid-Based Cytology Images to Discriminate Malignancy and Histological Types of Non-Small-Cell Lung Cancer.
Pathobiology : journal of immunopathology, molecular and cellular biology
Aug 28, 2024
INTRODUCTION: Artificial intelligence image recognition has applications in clinical practice. The purpose of this study was to develop an automated image classification model for lung cancer cytology using a deep learning convolutional neural networ...
A prognostic biomarker of disulfidptosis constructed by machine learning framework model as potential reporters of pancreatic adenocarcinoma.
Cellular signalling
Aug 28, 2024
BACKGROUND: Pancreatic adenocarcinoma (PAAD), known for its high lethality, has not been thoroughly explored in terms of its mechanisms and patterns of immune infiltration. Disulfidptosis, a newly identified mode of cell death, is likely associated w...
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