Oncology/Hematology

Artificial Intelligence Design for Race-Based Prostate Cancer Stage Classification With Multilayer Perceptron: Feature Selection Optimization Approach.

BACKGROUND: Prostate cancer progression exhibits significant variability influenced by biological and racial factors. DNA methylation profiling has shown potential in early cancer detection, but its integration with machine learning across racially diverse populations remains limited. OBJECTIVE: This study aimed to develop a prostate cancer stage classifier for the majority White cohort using DNA ...

Automatic sleep staging from CPAP airflow using a dual fusion multi-period convolutional neural network.

BACKGROUND: Continuous Positive Airway Pressure (CPAP) therapy is the standard treatment for obstructive sleep apnea-hypopnea syndrome, yet its use as a passive sleep dynamics monitoring remains limited. CPAP devices record only airflow signals, called CPAP-flow, which constantly interact with the pressure delivered by the device. This interaction renders the signal vulnerable to device-related ar...

Indocyanine green fluorescence for intraoperative detection of liver tumours in minimally invasive surgery: protocol for the LIVERGREEN phase IV multicentre clinical trial.

INTRODUCTION: Liver tumours are a leading cause of global morbidity and mortality. Current diagnostic tools, including computed tomography (CT), magne...

AI-guided discovery of the IRF4-PAICS-LDHA axis as a multitarget hub linking tumor metabolism to CD8+ T cell exhaustion in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) features an immunosuppressive tumor microenvironment (TME), yet the molecular drivers connecting metabolic repro...

Nanoparticle-based mechanistic and multifunctional strategies for targeted osteosarcoma therapy.

Osteosarcoma is the most common malignant bone tumor in children and adolescents, usually affecting the long bones of the limbs. Despite progress in s...

A vision-language foundation model improves preoperative diagnosis of follicular thyroid neoplasms using ultrasound images.

Preoperative discrimination between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) remains challenging, as imaging and cytolo...

Deep learning inference of cell type-specific gene expression from breast tumor histopathology.

Cell type-specific gene expression from single-cell RNA sequencing (RNA-seq) is valuable for breast cancer precision oncology but available cohorts ar...

LungNet: Leveraging state-space models with SE-enhanced skip connections for precise CT-based lung lesion segmentation.

Lung cancer, which accounted for 2.48 million new cases and 1.82 million deaths worldwide in 2022, continues to be the most lethal cancer across the g...

Likelihood-free parameter inference for spatiotemporal stochastic biological models using neural posterior estimation.

Cell migration is a key biological process underlying wound healing, tissue development, and cancer metastasis, yet calibrating mathematical models of...

MUSIOMICS: A multi-region radiomics framework that outperforms single-region analysis in classifying malignant pulmonary nodules.

BACKGROUND AND OBJECTIVE: Radiomic studies in lung cancer have primarily analyzed single-domain features extracted separately from intranodular (Zone-...

X2Shape: CT-free 3D multi-organ reconstruction with biplanar X-rays.

Reconstructing three-dimensional (3D) anatomy from routine X-ray imaging remains a long-standing challenge, promising high accessibility and minimal r...

Assessment of high- and low-risk histopathologic subtypes of basal cell carcinoma using artificial intelligence and dermatologist evaluation.

BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, and accurate histopathologic risk stratification is essential for treatment sel...

From pathogenesis to precision medicine in systemic lupus erythematosus: Emerging biomarkers and targeted interventions.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by immune dysregulation, autoantibody production, and chron...

Diagnostic performance of deep learning models on ultrasound images for distinguishing benign from malignant ovarian cysts.

BACKGROUND: Ovarian cysts are a common pelvic disorder in women, and accurate differentiation between benign and malignant types is essential for guid...

Development and validation of an MRI-based clinical-radiomics nomogram for predicting lymph node metastasis in non-small cell lung cancer.

Epigenetic Instability-Based Metrics in Cell-Free DNA for Early Cancer Detection.

PURPOSE: Cancers present significant DNA methylation changes, which arise in a stochastic manner, marked by extensive epigenetic variation, indicative...

Update on pleural mesothelioma.

PURPOSE OF REVIEW: Pleural mesothelioma remains a universally lethal cancer with a rising global burden. This underscores the need for pulmonologists ...

Integrated machine learning algorithms for prediction of prognosis in ovarian cancer patients based on mitochondrial-related genes.

Mitochondrial dysfunction drives ovarian cancer (OC) progression. This study constructed a robust prognostic model (MITO-OC) based on mitochondria-rel...

Recent Advances in Analytical Techniques for Cancer Diagnostics and Therapeutics: Combining State-of-the-Art Technologies for Precision Oncology.

Cancer remains a leading global health challenge, necessitating continuous advancements in diagnostics and therapeutics to enhance patient outcomes. A...

Machine learning-based multi-omic analysis identifies CEP55, DLGAP5, and EZH2 as regulated cell death biomarkers linked to immunotherapy resistance in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often exhibits limited responsiveness to immune checkpoint inhibitors (ICIs), largely due to an immunosuppressive tumor...