Other Cancers

Automated model-based lesion tracking in CT: colorectal liver metastases as a use case for development and performance analysis.

OBJECTIVE: To develop and evaluate an automated CT liver lesion-tracking algorithm that matches lesions over time, detects new metastases, and reports per‑lesion confidence to support response assessment. MATERIALS AND METHODS: The study included 87 adults with unresectable colorectal liver metastases (CRLM) who had baseline and 8-week follow-up contrast-enhanced CT. Three radiologists generated a...

Deep learning-driven discovery of anti-metastatic phytochemicals targeting MMP-1 in breast cancer via advanced contrastive learning and structural attention.

Matrix metalloproteinase-1 (MMP-1) is a key enzyme that drives extracellular matrix degradation and facilitates breast cancer progression, invasion, and metastasis. This abnormal MMP-1 activity is linked to worse patient outcomes and also improved progression of tumor, which promotes critical therapeutic target. However, recent deep learning approaches are utilized still unable to fully capture mo...

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) vaccinati...

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...

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 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...

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...

Label-Free Prediction of EGFR Mutation Status Using Fluorescence Lifetime Imaging and Deep Learning in Lung Adenocarcinoma.

UNLABELLED: Accurate prediction of epidermal growth factor receptor (EGFR) mutations is essential for guiding targeted therapy in non-small cell lung ...

Machine learning modeling to predict HCC locations in cirrhotic patients undergoing MRI - a proof-of-concept study.

PURPOSE: Current hepatocellular carcinoma (HCC) surveillance guidelines rely on manually defined LI-RADS (Liver Imaging Reporting and Data System) fea...

A machine learning-guided epithelial plasticity score refines prognostication and immune-context stratification in muscle-invasive bladder cancer.

PURPOSE: Muscle-invasive bladder cancer (MIBC) remains biologically heterogeneous, and clinicopathological variables do not fully capture epithelial-s...

Examining explainable artificial intelligence in TNM staging with PET-CT: a user-centred observation study.

PURPOSE: Artificial intelligence (AI) is increasingly proposed as a solution to improve efficiency in radiology and nuclear medicine, particularly in ...

Pharmacogenomics in oncology: mutation-targeted therapy and biomarker integration in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common cancer-related cause of death among all countries globally, mostly because of late diagnosis, he...

Disease-modifying antirheumatic drugs (DMARDs) for rheumatoid arthritis after failure of biologic or targeted synthetic therapy: a systematic review and network meta-analysis.

RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...