Oncology/Hematology

Revolutionizing breast cancer immunotherapy by integrating AI and nanotechnology approaches: review of current applications and future directions.

Breast cancer (BC) is still the most diagnosed cancer for females with an increased focus on immunot...

Multi-Omics-Based Characterization of DNA Methylation Episignatures for Papillary Thyroid Cancer in a Chinese Population.

Thyroid cancer is the most common endocrine malignancy, with papillary thyroid cancer (PTC) account...

Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis.

Sepsis is a systemic inflammatory response syndrome that predisposes to severe lung infections (SeAL...

Artificial intelligence in endoscopy and colonoscopy: a comprehensive bibliometric analysis of global research trends.

BACKGROUND: Artificial intelligence (AI) has revolutionized the field of gastroenterology, particula...

Optimal Res-UNET architecture with deep supervision for tumor segmentation.

BACKGROUND: Brain tumor segmentation is critical in medical imaging due to its significance in accur...

Integrative transcriptomics and single-cell transcriptomics analyses reveal potential biomarkers and mechanisms of action in papillary thyroid carcinoma.

OBJECTIVE: Papillary thyroid carcinoma (PTC) has a high recurrence rate and lacks reliable diagnosti...

Two decades of progress in gastric cancer peritoneal metastasis: a bibliometric perspective on molecular mechanisms and therapeutic innovations.

BACKGROUND: Gastric cancer (GC) is the fifth most common malignant tumor worldwide. The peritoneum i...

Graph-based analysis of histopathological images for lung cancer classification using GLCM features and enhanced graph.

Lung cancer remains a leading cause of global cancer mortality, demanding precise diagnostic tools f...

Random splicing assisted deep learning for breast cancer cell line classification via Raman spectroscopy.

Raman spectroscopy extracts rich biochemical information on a single cell, demonstrating significant...

Discovery of novel diagnostic biomarkers of hepatocellular carcinoma associated with immune infiltration.

OBJECTIVE: Diagnosis of hepatocellular carcinoma (HCC) remains challenging for clinicians. Machine l...

Analysis of the clinical tumor stage and survival prognosis of rectal cancer patients on the basis of deep learning and imaging characteristics: An observational study.

Leveling Up: Harnessing Cutting-Edge Technology to Enhance Oncology Education and Learning.

The integration and utilization of digital media, gamified learning strategies, and artificial intel...

Navigating the future of fertility preservation: advanced predictive strategies for treatment outcomes of endometrial atypical hyperplasia and carcinoma.

Due to the decreasing age of onset and the postponement of childbearing, there is a growing number o...

Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care.

Musculoskeletal tumors present a diagnostic challenge due to their rarity, histological diversity, a...

Optimizing Artificial Intelligence Thresholds for Mammographic Lesion Detection: A Retrospective Study on Diagnostic Performance and Radiologist-Artificial Intelligence Discordance.

Artificial intelligence (AI)-based systems are increasingly being used to assist radiologists in de...

Foundation model embeddings for quantitative tumor imaging biomarkers.

Foundation models are increasingly used in medical imaging, yet their ability to extract reliable qu...

Reevaluating Feature Selection in Machine Learning-Based Radiomics for Hepatocellular Carcinoma: Bridging the Gap Between Predictive Accuracy and Biological Relevance.

A cell-interacting and multi-correcting method for automatic circulating tumor cells detection.

Sensitive detection of circulating tumor cells (CTCs) from peripheral blood can serve as an effectiv...

CT-Based Radiomics for Predicting PD-L1 Expression in Non-small Cell Lung Cancer: A Systematic Review and Meta-analysis.

BACKGROUND AND PURPOSE: The efficacy of immunotherapy in non-small cell lung cancer (NSCLC) is intri...

Ultrasound image-based contrastive fusion non-invasive liver fibrosis staging algorithm.

OBJECTIVE: The diagnosis of liver fibrosis is usually based on histopathological examination of live...

A protein-based classifier for differentiating follicular thyroid adenoma and carcinoma.

Differentiating follicular thyroid adenoma (FTA) from carcinoma (FTC) remains challenging due to sim...