Oncology/Hematology

Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks.

This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multi...

Integrating artificial intelligence into functional and aesthetic analysis of lip reconstruction after tumor resection.

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma.

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LU...

Artificial intelligence assisted diagnosis of chronic lymphocytic leukemia in a historic pediatric case using large language models.

Artificial intelligence assisted ultrasound for the non-invasive prediction of axillary lymph node metastasis in breast cancer.

PURPOSE: A practical noninvasive method is needed to identify lymph node (LN) status in breast cance...

Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma.

BACKGROUND: Although there has been some progress in the treatment of primary uveal melanoma (UVM), ...

Explainable machine learning models for early gastric cancer diagnosis.

Gastric cancer remains a significant global health concern, with a notably high incidence in East As...

An attention-based deep learning for acute lymphoblastic leukemia classification.

The bone marrow overproduces immature cells in the malignancy known as Acute Lymphoblastic Leukemia ...

Deciphering dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning.

This study investigates the altered expression and CpG methylation patterns of histone demethylase ...

Deep learning model based on contrast-enhanced ultrasound for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma.

OBJECTIVES: To establish and validate a non-invasive deep learning (DL) model based on contrast-enha...

Efficient application of deep learning-based elective lymph node regions delineation for pelvic malignancies.

BACKGROUND: While there are established international consensuses on the delineation of pelvic lymph...

RACGAP1 is a pivotal gene in lung adenocarcinoma-associated membranous nephropathy: Based on comprehensive bioinformatics analysis and machine learning.

BACKGROUND: This study performs a detailed bioinformatics and machine learning analysis to investiga...

Using deep learning for predicting the dynamic evolution of breast cancer migration.

BACKGROUND: Breast cancer (BC) remains a prevalent health concern, with metastasis as the main drive...

Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making.

Skin cancer is a type of cancer disease in which abnormal alterations in skin characteristics can be...

AG-MSTLN-EL: A Multi-source Transfer Learning Approach to Brain Tumor Detection.

The analysis of medical images (MI) is an important part of advanced medicine as it helps detect and...

Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer.

The tissue diagnosis of adenocarcinoma and intraductal carcinoma of the prostate includes Gleason gr...

Prediction of leukemia peptides using convolutional neural network and protein compositions.

Leukemia is a type of blood cell cancer that is in the bone marrow's blood-forming cells. Two types ...

Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.

BACKGROUND: Artificial intelligence (AI) using deep learning systems has recently been utilized in v...

DeepDRA: Drug repurposing using multi-omics data integration with autoencoders.

Cancer treatment has become one of the biggest challenges in the world today. Different treatments a...

Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.

BACKGROUND: Clinical decision-making in oncology is a complex process influenced by numerous disease...

Machine learning models including preoperative and postoperative albumin-bilirubin score: short-term outcomes among patients with hepatocellular carcinoma.

BACKGROUND: We sought to assess the impact of various perioperative factors on the risk of severe co...