Oncology/Hematology

Colon Cancer

Latest AI and machine learning research in colon cancer for healthcare professionals.

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TFCNet: A texture-aware and fine-grained feature compensated polyp detection network.

PURPOSE: Abnormal tissue detection is a prerequisite for medical image analysis and computer-aided d...

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study.

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparamet...

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved ap...

Assessment of the quality of online patient-oriented information on robotic colorectal surgery.

With advances in modern medicine, there is a constant need for accurate and up-to-date readily avail...

The rise of robotic colorectal surgery: better for patients and better for surgeons.

Robotic colorectal surgery represents a major technological advancement in the treatment of patients...

Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.

BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been dev...

Role of the artificial intelligence in the management of T1 colorectal cancer.

Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph n...

Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.

INTRODUCTION: Both artificial intelligence (AI) and distal attachment devices have been shown to imp...

Development and multicenter validation of deep convolutional neural network-based detection of colorectal cancer on abdominal CT.

OBJECTIVES: This study aims to develop computer-aided detection (CAD) for colorectal cancer (CRC) us...

Deep Learning Enabled SERS Identification of Gaseous Molecules on Flexible Plasmonic MOF Nanowire Films.

Through the capture of a target molecule at the metal surface with a highly confined electromagnetic...

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor...

Impact of AI-aided colonoscopy in clinical practice: a prospective randomised controlled trial.

OBJECTIVE: Colorectal cancer (CRC) has a significant role in cancer-related mortality. Colonoscopy, ...

Impact of study design on adenoma detection in the evaluation of artificial intelligence-aided colonoscopy: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Randomized controlled trials (RCTs) have reported that artificial intelligence ...

Medical image fusion based on machine learning for health diagnosis and monitoring of colorectal cancer.

With the rapid development of medical imaging technology and computer technology, the medical imagin...

A computer-aided system improves the performance of endoscopists in detecting colorectal polyps: a multi-center, randomized controlled trial.

BACKGROUND: Up to 45.9% of polyps are missed during colonoscopy, which is the major cause of post-co...

DARDN: A Deep-Learning Approach for CTCF Binding Sequence Classification and Oncogenic Regulatory Feature Discovery.

Characterization of gene regulatory mechanisms in cancer is a key task in cancer genomics. CCCTC-bin...

Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their siz...

Integrating clinical and cross-cohort metagenomic features: a stable and non-invasive colorectal cancer and adenoma diagnostic model.

Dysbiosis is associated with colorectal cancer (CRC) and adenomas (CRA). However, the robustness of...

Machine Learning Developed a MYC Expression Feature-Based Signature for Predicting Prognosis and Chemoresistance in Pancreatic Adenocarcinoma.

MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. How...

Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach.

BACKGROUND: Accurate estimation of the long-term risk of recurrence in patients with non-metastatic ...

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