Oncology/Hematology

Advances in endometrial cancer screening: a comprehensive review of current methods and emerging technologies.

Endometrial cancer represents a major global health concern, with rising incidence particularly in developed countries despite declining mortality rates. This comprehensive review examines the evolution of endometrial cancer screening techniques, encompassing traditional methods, emerging technologies, and integrated approaches. Traditional screening methods including transvaginal ultrasound and h...

Predictive Modeling of Cancer Information Overload and Screening Attitudes: A Cross-Sectional Study.

OBJECTIVE: To explore the association between cancer information overload and attitudes toward cancer screening among internal medicine patients. AIMS: To identify predictors of screening attitudes using statistical and machine learning models. METHODS: A cross-sectional study was conducted with 410 internal medicine outpatients. Data were collected using the Cancer Information Overload Scale and ...

Emerging nanoparticle-based therapies for pancreatic cancer: Current clinical landscape.

Pancreatic cancer, particularly ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal subtypes due to late diagnosis, the absence of e...

Preoperative Identification of Lymph Node Metastasis in Colorectal Cancer Using Noninvasive Circulating Tumor DNA Methylation Signatures: Results From a Prospective Study.

BACKGROUND: Lymph node metastasis is important for the management and surgical procedures of patients with colorectal cancer. Preoperative identificat...

Deep learning discriminates thymic epithelial tumors' histological subtypes using digital pathology.

BACKGROUND: Thymic epithelial tumors (TETs) are rare malignancies that pose significant diagnostic challenges due to their heterogeneous histological ...

Developing explainable machine learning models from biochemical and clinical data to predict all-cause and cause-specific mortality in CVD-cancer comorbidity: A longitudinal study based on NHANES.

BACKGROUND: Cardiovascular disease (CVD) and cancer are leading causes of mortality, often coexisting in aging populations. Patients with comorbiditie...

CIA-net: Cross-modality interaction and aggregation network for ovarian tumor segmentation from multi-modal MRI.

Magnetic resonance imaging (MRI) is an essential examination for ovarian cancer, in which ovarian tumor segmentation is crucial for personalized diagn...

Tumoroid-derived extracellular vesicles for prognosis and therapeutics: A valuable tool in precision medicine.

Precision medicine has transformed healthcare by tailoring treatment plans to an individual's genetic profile, in contrast to standardized therapies. ...

Enhancing clinicians' trust in large language models via transparent source attribution: A randomized controlled evaluation in uro-oncology.

INTRODUCTION: Large language models (LLMs) are utilized to answer queries in urology and oncology, yet the performance is limited due to outdated data...

Revolutionizing Liver Imaging: Artificial Intelligence-Driven Advances in Diagnostics and Staging.

Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhanced diagnostic accuracy, efficiency, and reproducibi...

Machine Learning for diagnosis of malignant thyroid nodules based on thyroid ultrasound: Systematic review and meta-analysis of studies with external datasets.

INTRODUCTION: Optimizing the diagnostic approach to thyroid nodules remains a crucial challenge. Ultrasound-based risk stratification systems such as ...

Accelerating Prostate Cancer Detection Through Histopathological Image Analysis Using Artificial Intelligence.

Prostate cancer is a prevalent and serious health concern, ranking among the most frequently diagnosed cancers and a leading cause of cancer-related d...

Super-resolution deep learning reconstruction improves brain MRI quality and detection of metastases.

PURPOSE: Accurate identification of brain metastases is critical for determining prognosis and guiding treatment. Deep learning reconstruction (DLR) e...

MethylMSI: Prediction of microsatellite instability based on DNA methylation profile and SVM model.

Microsatellite instability (MSI) has gained increasing attention as a promising biomarker for cancer immunotherapy in diverse cancer types. As a resul...

Modern integrative prostate cancer diagnostics.

PURPOSE OF REVIEW: To review contemporary applications, performance, and implementation challenges of artificial intelligence (AI) in the radiological...

Algorithm guided personalized T cell therapy: machine learning unlocks next generation TCR engineered immunotherapy.

Recent advances in cancer nanomedicine: From smart targeting to personalized therapeutics - pioneering a new era in precision oncology.

Cancer nanomedicine has evolved from the 1995 landmark approval of Doxil® into a programmable platform of precision oncology. The field now progresses...

The best from both disciplines: integrating human and microbial signatures from whole genome sequencing to advance cancer diagnostics.

Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current ap...

Decoding strategies for enhancing immunotherapy in head and neck squamous cell carcinoma.

Immune checkpoint inhibitors have partially improved treatment outcomes for patients with head and neck squamous cell carcinoma (HNSCC), but the respo...

PD-L1 expression combined with immune phenotype is a potential predictor of outcome with PD-1 inhibitor monotherapy in patients with recurrent or metastatic head and neck squamous cell carcinoma.

OBJECTIVE: Programmed cell death-ligand 1 (PD-L1) expression and immune phenotype (IP) are potential predictive biomarkers for immune checkpoint inhib...