Oncology/Hematology

Efficacy of a whole slide image-based prediction model for lymph node metastasis in T1 colorectal cancer: A systematic review.

BACKGROUND AND AIM: Accurate stratification of the risk of lymph node metastasis (LNM) following end...

Machine learning algorithms and biomarkers identification for pancreatic cancer diagnosis using multi-omics data integration.

PURPOSE: Pancreatic cancer is a lethal type of cancer with most of the cases being diagnosed in an a...

SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification.

The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accuratel...

Impact of the number of dissected lymph nodes on machine learning-based prediction of postoperative lung cancer recurrence: a single-hospital retrospective cohort study.

BACKGROUND: The optimal number of lymph nodes to be dissected during lung cancer surgery to minimise...

BSNEU-net: Block Feature Map Distortion and Switchable Normalization-Based Enhanced Union-net for Acute Leukemia Detection on Heterogeneous Dataset.

Acute leukemia is characterized by the swift proliferation of immature white blood cells (WBC) in th...

Raman fiber-optic probe for rapid diagnosis of gastric and esophageal tumors with machine learning analysis or similarity assessments: a comparative study.

Gastric and esophageal cancers, the predominant forms of upper gastrointestinal malignancies, contri...

Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagn...

Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

Randomized controlled trial of an artificial intelligence diagnostic system for the detection of esophageal squamous cell carcinoma in clinical practice.

BACKGROUND: Artificial intelligence (AI) has made remarkable progress in image recognition using dee...

Effectiveness of artificial intelligence assisted colonoscopy on adenoma and polyp miss rate: A meta-analysis of tandem RCTs.

BACKGROUND AND AIMS: One-fourth of colorectal neoplasia is missed at screening colonoscopy, represen...

Quantifying and visualising uncertainty in deep learning-based segmentation for radiation therapy treatment planning: What do radiation oncologists and therapists want?

BACKGROUND AND PURPOSE: During the ESTRO 2023 physics workshop on "AI for the fully automated radiot...

Efficient bladder cancer diagnosis using an improved RIME algorithm with Orthogonal Learning.

Bladder cancer (BC) diagnosis presents a critical challenge in biomedical research, necessitating ac...

Artificial intelligence (AI) applications in improvement of IMRT and VMAT radiotherapy treatment planning processes: A systematic review.

INTRODUCTION: Radiotherapy is a common option in the treatment of many types of cancer. Intensity-Mo...

Machine learning-based discovery of UPP1 as a key oncogene in tumorigenesis and immune escape in gliomas.

INTRODUCTION: Gliomas are the most common and aggressive type of primary brain tumor, with a poor pr...

Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.

BACKGROUND: Hepatocellular carcinoma (HCC) is highly aggressive, with delayed diagnosis, poor progno...

A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma Based on CT Images.

This study developed and validated a deep learning-based diagnostic model with uncertainty estimatio...

Skin Cancer Detection in Diverse Skin Tones by Machine Learning Combining Audio and Visual Convolutional Neural Networks.

INTRODUCTION: Skin cancer (SC) is common in fair skin (FS) at a 1:5 lifetime incidence for nonmelano...

Machine Learning-Enabled Fuhrman Grade in Clear-cell Renal Carcinoma Prediction Using Two-dimensional Ultrasound Images.

OBJECTIVE: Accurate assessment of Fuhrman grade is crucial for optimal clinical management and perso...

Identification of macrotrabecular-massive hepatocellular carcinoma through multiphasic CT-based representation learning method.

BACKGROUND: Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive subt...

Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy i...

From Biosensors to Robotics: Pioneering Advances in Breast Cancer Management.

Breast cancer stands as the most prevalent form of cancer amongst females, constituting more than on...