Oncology/Hematology

Colon Cancer

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

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GFPrintâ„¢: A machine learning tool for transforming genetic data into clinical insights.

The increasing availability of massive genetic sequencing data in the clinical setting has triggered...

Role of Artificial Intelligence for Colon Polyp Detection and Diagnosis and Colon Cancer.

The broad use of artificial intelligence (AI) and its various applications have already shown signif...

CLMS: Bridging domain gaps in medical imaging segmentation with source-free continual learning for robust knowledge transfer and adaptation.

Deep learning shows promise for medical image segmentation but suffers performance declines when app...

MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with Application in Colonic Polyp Image Segmentation.

Accurate polyp image segmentation is of great significance, because it can help in the detection of ...

Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in ar...

Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

There exist significant challenges for lung adenocarcinoma (LUAD) due to its poor prognosis and lim...

In-context learning enables multimodal large language models to classify cancer pathology images.

Medical image classification requires labeled, task-specific datasets which are used to train deep l...

Automatic TNM staging of colorectal cancer radiology reports using pre-trained language models.

BACKGROUND AND OBJECTIVE: Colorectal cancer is one of the major causes of cancer death worldwide. Es...

Non-invasive multiple cancer screening using trained detection canines and artificial intelligence: a prospective double-blind study.

The specificity and sensitivity of a simple non-invasive multi-cancer screening method in detecting ...

Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer.

BACKGROUND: Tumor Mutational Burden (TMB) have emerged as pivotal predictive biomarkers in determini...

In vivo evaluation of complex polyps with endoscopic optical coherence tomography and deep learning during routine colonoscopy: a feasibility study.

Standard-of-care (SoC) imaging for assessing colorectal polyps during colonoscopy, based on white-li...

SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer.

Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlight...

AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images.

The acurate segmentation and classification of nuclei in histological images are crucial for the dia...

Machine learning model for early prediction of survival in gallbladder adenocarcinoma: A comparison study.

The prognosis for gallbladder adenocarcinoma (GBAC), a highly malignant cancer, is not good. In orde...

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