Other Cancers

Deep learning reconstruction-applied PROPELLER diffusion-weighted imaging in uterine malignancies: a comparison study with MUSE.

PURPOSE: To compare the image quality of diffusion-weighted imaging (DWI) between deep learning reconstruction (DLR)-applied Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) and MUltiplexed Sensitivity Encoding (MUSE) sequences in MRI of uterine malignancies. MATERIALS AND METHODS: This retrospective study included 66 MRI examinations of 48 patients. The coh...

Scientific evidence of commercial artificial intelligence products for pulmonary nodule assessment on CT scans: a systematic review.

OBJECTIVES: This systematic review evaluates the available evidence on the efficacy of commercially available AI-software applications for lung nodule assessment on CT scans. MATERIALS AND METHODS: In adherence to PRISMA guidelines, a thorough search of electronic databases was conducted (January 2012-November 2024) to identify studies on CE-marked and/or FDA-cleared AI-based systems for evaluatin...

From Symptom Control to Precision Supportive Oncology: Integrating Artificial Intelligence in Supportive Oncology for Gastrointestinal Cancers.

PURPOSE OF REVIEW: Gastrointestinal (GI) cancers are among the most common malignancies worldwide and impose a substantial symptom burden from diagnos...

Integrative machine learning and multi-omics identify a centromere gene signature and validate B3GALT4 as a tumor suppressor in osteosarcoma.

Centromere-associated genes are linked to genomic instability and tumor progression, yet their significance and immunological roles in osteosarcoma (O...

Differentiating Radiotherapy-Specific Distress From General Cancer Distress: Natural Language Processing Analysis of Patient Narratives.

BACKGROUND: Psychological distress is common among patients with cancer, and it negatively impacts treatment adherence and quality of life. Radiothera...

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...

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, a...

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...

Toward robust histopathology imaging: An unsupervised framework for artifact detection, localization, and restoration.

Whole Slide Images are central to modern pathology and computational histopathology. However, tissue processing and slide scanning can introduce artif...

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...