Oncology/Hematology

Global Trends and Insights in Cervical Cancer Research: A Bibliometric Analysis from 2000 to 2024.

Cervical cancer is the fourth most common malignant disease in women worldwide. Although the promotion and use of human papillomavirus (HPV) vaccinations have to some extent reduced the incidence of cervical cancer, problems persist, particularly in low- and middle-income nations. This bibliometric study, which shows the worldwide landscape of cervical cancer research from 2000 to 2024 through sci...

Spectral CT in radiotherapy: physics, principles, clinical applications, and future outlooks.

BACKGROUND: Conventional single-energy CT (SECT) is limited in differentiating materials with similar Hounsfield units. Unlike previous reviews that mainly focused on the physics and general oncologic applications of dual-/multi-energy CT, this review evaluates spectral CT from a radiotherapy-oriented perspective, emphasizing its role in simulation, contouring, dose calculation, treatment monitori...

Computational modeling of regulated protein conformational transitions.

Conformational transitions are not accidents; they are the currency of regulation. Cells actively spend energy through adenosine triphosphate (ATP) tu...

Application of cell-free RNA in liquid biopsy.

Cell free RNA (cfRNA) based liquid biopsy is pushing noninvasive diagnostics forward, moving the field from a static view focused on genomics into a m...

Artificial Intelligence-Based Computer-Aided Detection in Breast Cancer Diagnosis: Variation by Breast Density, Imaging Feature, and Tumor Characteristics.

RATIONALE AND OBJECTIVES: To determine whether an FDA-approved artificial intelligence computer-aided detection and diagnosis (AI-CAD) system assigns ...

Integrative multi-omics reveals MHC class II-mediated neuroinflammation and systemic metabolic dysregulation as transdiagnostic drivers in major brain disorders.

Psychiatric, neurodevelopmental, and neurodegenerative disorders, including Alzheimer's disease (AD), attention-deficit/hyperactivity disorder (ADHD),...

Machine learning-based prognosis and early death prediction in de novo stage IV breast cancer patients with bone metastasis: a SEER database and multicentre retrospective study.

Bone is the most common site of distant metastasis in breast cancer (BC), and the development of bone metastasis (BM) is associated with reduced survi...

Improving preoperative risk stratification in colorectal liver metastases: a multi-institutional evaluation of multimodal prediction models.

Reliable prognostic models of death or liver recurrence following resection of colorectal liver metastases are critical to stratify patients for treat...

Deep learning-based segmentation and subtype prediction of renal cell carcinoma on contrast-enhanced CT.

Accurate preoperative discrimination of renal cell carcinoma (RCC) subtypes is critical for treatment stratification. We aimed to develop and validate...

Enhancing mortality prediction in septic ICU patients with malignancies through ensemble machine learning: a retrospective cohort study.

Sepsis remains a leading cause of mortality in the intensive care unit (ICU), and patients with underlying malignancies are disproportionately affecte...

Multi-omics fusion with machine learning enables robust prediction of treatment response in ovarian cancer for precision population health.

Inter-patient heterogeneity complicates predicting treatment response in ovarian cancer (OC). We developed OMICS-FUSE, an early-fusion multi-omics pre...

Multi-omics machine learning-driven investigation of super-enhancers signatures and prognostic biomarkers in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common histological subtype of malignant lung tumors, characterized by high incidence and mortality rates. Supe...

Explainable Ensemble Learning With Stain Normalization and Deep Feature Extraction for Acute Lymphoblastic Leukaemia Classification.

Acute lymphoblastic leukaemia (ALL), a common form of cancer, remains a life-threatening condition that affects individuals worldwide, including both ...

Perithyroidal Adipose Tissue Drives Thyroid Tumorigenesis through Adipokine Signaling and Immune Suppression.

The perithyroidal adipose tissue (PAT), given its direct anatomical proximity to the thyroid gland, has long been postulated as a modulator of the thy...

MiracleNet: A Biologically Interpretable Machine Learning Model for Resected Non-small-cell Lung Cancer.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Accurate prediction of relapse is notoriously difficult, posing s...

Deep convolutional GAN and hypernet-based neural architecture search for brain tumor diagnosis detection and classification.

Brain tumors are complex and life-threatening conditions that require accurate and efficient diagnostic approaches. However, existing approaches often...

A Radiomics-Driven Model to Distinguish Between Clinically Similar Myxopapillary Ependymomas and Lumbosacral Schwannomas.

BACKGROUND AND OBJECTIVES: Myxopapillary ependymomas (MPE) and intradural lumbosacral schwannomas may be challenging to distinguish based on presentin...

Machine learning-based prognostic model and single-cell transcriptomic integration for identifying brain metastasis-associated malignant subpopulations and potential therapeutic targets in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a highly prevalent and lethal form of lung cancer. Brain metastasis (BrM) is a major cause of mortality in p...

Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.

BACKGROUND: Understanding how epigenome variation contributes to gene expression in disease and development is a fundamental challenge. Regulatory reg...

Patient understanding of AI-simplified oncology imaging reports requires further validation.

Ribeiro and colleagues offer timely evidence that large language models can make oncology imaging reports more accessible to radiologists and patient ...