Other Cancers

Intrinsically disordered proteins and liquid-liquid phase separation in drug discovery.

Intrinsically disordered proteins (IDPs) and their involvement in liquid-liquid phase separation (LLPS) have reshaped our understanding of how cells organize biochemical reactions in space and time. Unlike structured proteins, IDPs populate highly dynamic conformational ensembles that promote weak, multivalent interactions and enable the formation of biomolecular condensates (BCs). When these phas...

Performance across different versions of an artificial intelligence model for screen-reading of mammograms.

OBJECTIVES: Studies have reported promising results regarding artificial intelligence (AI) as a tool for improved mammographic screening interpretive performance. We analyzed AI malignancy risk scores from two versions of the same commercial AI model. MATERIALS AND METHODS: This retrospective cohort study used data from 117,709 screening examinations performed in BreastScreen Norway 2009-2018. The...

Lesion-level prediction of local recurrence after stereotactic radiotherapy for brain metastases using machine learning and mixed-effects modeling.

BACKGROUND: The aim of this study was to identify and validate clinically meaningful predictors of local treatment failure (LTF) after stereotactic ra...

Randomized evidence on AI-enabled personalized treatment planning for adults with depressive-anxiety Spectrum disorders: A systematic review and Meta-analysis.

BACKGROUND: AI-enabled personalized treatment planning may improve outcomes by tailoring care, yet its clinical impact across modalities remains uncer...

NEIL1 suppresses ROS accumulation to promote temozolomide resistance and malignant progression in glioma cells.

BACKGROUND: Glioma is the most common malignant primary brain tumor. Temozolomide (TMZ) is the standard first-line chemotherapy, but its efficacy is s...

Programmable Smart CAR-T design: A new paradigm in precision immunotherapy driven by logic gates, conditional activation, allogeneic strategies, and artificial intelligence.

Chimeric antigen receptor T-cell (CAR-T) therapy has achieved unprecedented success in hematological malignancies but faces formidable challenges in s...

A research on applying the diffusion model algorithm for Infrared and Raman spectroscopy data augmentation to improve the accuracy of diseases.

In recent years, Raman and Infrared spectroscopy have become important tools in disease diagnosis due to their high sensitivity and non-invasive detec...

CTSB-positive tumor-associated macrophages shape prognosis and therapeutic response in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) remains a major clinical challenge in assessment of clinical outcomes and therapeutic response. Although tumor-...

Shap-interpretable predictive modeling of microvascular invasion and early recurrence in hepatocellular carcinoma using MRI habitat imaging combined with clinical features.

OBJECTIVE: To develop and validate an integrated model combining Gd-EOB-DTPA-enhanced MRI habitat imaging with clinical features for preoperative pred...

C2HFusion: Clinical context-driven hierarchical fusion of multimodal data for personalized and quantitative prognostic assessment in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Accurate prognostic modeling enables reliable risk stratification to identi...

Machine learning-guided identification of metastasis-associated miRNAs and their integration into a PFI-based cox risk score and nomogram.

BACKGROUND: Metastasis drives mortality in breast invasive carcinoma. We sought miRNA biomarkers that (i) discriminate metastatic potential, (ii) stra...

Machine learning assisted raman spectroscopy for the classification of ovarian cancer cells.

Ovarian cancer is one of the most lethal gynecological malignancies, asymptomatic early progression, ineffective screening, and high histological hete...

Utilizing artificial intelligence for the diagnosis of ocular surface squamous neoplasia with ultrasound biomicroscopy images.

PURPOSE: This study aims to develop an artificial intelligence (AI) model to assist ophthalmologists in distinguishing ocular surface squamous neoplas...

AI-based assessment of brain volume decrease after treatment with stereotactic radiosurgery versus whole brain radiotherapy.

BACKGROUND: Radiotherapy is a cornerstone in the treatment of brain metastases, but its mid- and long-term impact on brain parenchyma remains poorly u...

A multi-target therapeutic framework for Alzheimer's disease: an integrative mechanistic review.

BACKGROUND: Alzheimer's disease (AD) is increasingly recognized as a multifactorial network disorder in which amyloid and tau pathology interact with ...

Cross-omics interpretable neural network for discovery of molecular markers in prostate cancer.

Determining molecular markers that mediate clinically aggressive phenotypes in prostate cancer is a significant challenge. While traditional linear mo...

Interpretable machine learning-based prediction of liver metastasis risk in elderly patients with small cell lung Cancer: A study based on the SEER database and external validation in a Chinese cohort.

PURPOSE: Small cell lung cancer (SCLC) is a highly aggressive malignancy with a high incidence of liver metastases, particularly among elderly patient...

Emerging Diagnostic Indications for Endoscopic Ultrasound.

Endoscopic ultrasound (EUS) has evolved from a diagnostic imaging tool into a versatile platform that enables high-precision access, sampling, and the...

The use of digital gamification, extended reality, artificial intelligence, and integrated digital learning tools in palliative care education of undergraduate nurses: A systematic review.

BACKGROUND: Nurses are at the forefront of providing palliative care, playing a critical role in ensuring high-quality support for patients and their ...

Decoding Temporomandibular Disorders: Identifying Stage-Specific and Functional Patterns in the Articular Disc.

BACKGROUND: Despite affecting approximately 30% of the population, the pathogenesis of temporomandibular disorders (TMD) remains poorly understood. Co...