AIMC Topic: Adenocarcinoma
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Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.
Digestion
Jul 26, 2024
BACKGROUND: Artificial intelligence (AI) using deep learning systems has recently been utilized in various medical fields. In the field of gastroenterology, AI is primarily implemented in image recognition and utilized in the realm of gastrointestina...
Image Processing, Computer-Assisted
Sensitivity and Specificity
Humans
Adenocarcinoma
Colorectal Neoplasms
Artificial Intelligence
Endoscopy, Gastrointestinal
Diagnosis, Computer-Assisted
Stomach Neoplasms
Gastrointestinal Neoplasms
Deep Learning
Esophageal Neoplasms
Esophageal Squamous Cell Carcinoma
Endoscopy, Digestive System
Prospective and multi-reader evaluation of deep learning reconstruction-based accelerated rectal MRI: image quality, diagnostic performance, and reading time.
European radiology
Jul 17, 2024
OBJECTIVES: To evaluate deep learning reconstruction (DLR)-based accelerated rectal magnetic resonance imaging (MRI) compared with standard MRI.
Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.
Omics : a journal of integrative biology
Jul 9, 2024
Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and mortality rate, not to mention the marked interindividual variability in treatment outcomes and side effects. There is an urgent need for robust system...
Development of high-quality artificial intelligence for computer-aided diagnosis in determining subtypes of colorectal cancer.
Journal of gastroenterology and hepatology
Jun 26, 2024
BACKGROUND AND AIM: There are no previous studies in which computer-aided diagnosis (CAD) diagnosed colorectal cancer (CRC) subtypes correctly. In this study, we developed an original CAD for the diagnosis of CRC subtypes.
Evaluating the prognostic value of tumor deposits in non-metastatic lymph node-positive colon adenocarcinoma using Cox regression and machine learning.
International journal of colorectal disease
Jun 26, 2024
BACKGROUND: The 8th AJCC TNM staging for non-metastatic lymph node-positive colon adenocarcinoma patients(NMLP-CA) stages solely by lymph node status, irrespective of the positivity of tumor deposits (TD). This study uses machine learning and Cox reg...
Artificial intelligence (AI) systems for detection of Barrett's neoplasia: time to bridge domain gaps and explore human-AI interaction.
Endoscopy
Jun 18, 2024
Artificial Intelligence Imaging Diagnosis Using Super-Resolution and Three-Dimensional Shape for Lymph Node Metastasis of Low Rectal Cancer: A Pilot Study From a Single Center.
Diseases of the colon and rectum
Jun 11, 2024
BACKGROUND: Although accurate preoperative diagnosis of lymph node metastasis is essential for optimizing treatment strategies for low rectal cancer, the accuracy of present diagnostic modalities has room for improvement.
Male
Middle Aged
Pilot Projects
Imaging, Three-Dimensional
Lymph Nodes
Adenocarcinoma
Lymphatic Metastasis
Lymph Node Excision
Female
Aged
Adult
Multidetector Computed Tomography
Humans
Sensitivity and Specificity
Predictive Value of Tests
Proctectomy
Artificial Intelligence
Pelvis
Retrospective Studies
Rectal Neoplasms
Layer-selective deep representation to improve esophageal cancer classification.
Medical & biological engineering & computing
Jun 7, 2024
Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliabili...
Deep Learning for Histopathological Assessment of Esophageal Adenocarcinoma Precursor Lesions.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jun 1, 2024
Histopathological assessment of esophageal biopsies is a key part in the management of patients with Barrett esophagus (BE) but prone to observer variability and reliable diagnostic methods are needed. Artificial intelligence (AI) is emerging as a po...
Interpretable machine learning for predicting the response duration to Sintilimab plus chemotherapy in patients with advanced gastric or gastroesophageal junction cancer.
Frontiers in immunology
May 22, 2024
BACKGROUND: Sintilimab plus chemotherapy has proven effective as a combination immunotherapy for patients with advanced gastric and gastroesophageal junction adenocarcinoma (GC/GEJC). A multi-center study conducted in China revealed a median progress...
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