Cardiovascular

MRI-Based peritumoral radiomics for predicting recurrence risk in ER+/HER2- breast cancer.

Machine Learning-Based Prediction of Distant Recurrence Risk and Ribociclib Treatment Effect in HR+/HER2- Early Breast Cancer Using Real-World and NATALEE Data.

PURPOSE: Despite current standard-of-care endocrine therapy, distant recurrence remains a concern for patients with hormone receptor-positive (HR+)/HER2- early breast cancer (EBC). Understanding individual recurrence risk would aid in clinical decision-making. We used machine learning to identify risk factors and develop recurrence risk prediction models. EXPERIMENTAL DESIGN: Predictor variables w...

Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models.

Transcriptomic assays such as the PAM50-based ROR-P score guide recurrence risk stratification in non-metastatic, ER-positive, HER2-negative breast ca...

TomoRay cranial: synthesis of cranial CT imaging from biplanar radiographs using a generative adversarial network.

OBJECTIVES: Besides clinical examination, cranial CT plays a critical role in diagnostics in neurosurgery. In trauma cases or perioperatively, having ...

Automatic radiation-free evaluation of Cobb angle for spinal curvature based on fringe projection profilometry and deep learning technology.

OBJECTIVE: Pediatric scoliosis is the most prevalent spinal disorder, often leading to abnormal curvature and deformation of the spine. Early detectio...

BreastDCEDL: A standardized deep learning-ready breast DCE-MRI dataset of 2,070 patients.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is essential for monitoring breast cancer treatment response, yet deep learning progres...

Image Quality Assessment of Artificial Intelligence Iterative Reconstruction for Low-dose Bronchial Artery CTA in Preoperative Hemoptysis Patients.

OBJECTIVES: To investigate the feasibility and image quality of artificial intelligence iterative reconstruction (AIIR) for computed tomography angiog...

Comprehensive review on immunotherapy for hepatocellular carcinoma: Current status and future perspectives.

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, remains a major global health concern due to its high incidence and mort...

Externally validated knowledge-based planning model for machine learning-assisted radiation therapy treatment of high-grade glioma.

We have trained and externally validated a knowledge-based planning model for radiation therapy planning in the setting of high-grade glioma. Model pe...

Single-inspiratory quantitative CT nomogram for enhanced PRISm and COPD differentiation: a cross-sectional study with interpretable diagnostic boundaries.

BACKGROUND: Differentiating preserved ratio impaired spirometry (PRISm) from chronic obstructive pulmonary disease (COPD) is challenging. Traditional ...

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...

CT-free attenuation and scatter correction of [11C]CFT brain PET using a Bi-directional matching network.

Quantitative PET imaging requires accurate attenuation and scatter correction (ASC), but the standard CT-based method introduces additional radiation ...

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...

Machine Learning-Based Prediction Model for Delayed Chemotherapy-Induced Nausea and Vomiting in Pediatric Cancer: A Prospective Cohort Study.

BACKGROUND: Delayed chemotherapy-induced nausea and vomiting (CINV) in pediatric oncology patients is currently under-recognized. This study aims to d...

MRI-to-PET synthesis via deep learning for amyloid-β quantification in Alzheimer's disease.

OBJECTIVES: Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer's disease (AD), but its high cost and radiation exposure limit its u...

Chemo-prAIdict Breast: A deep learning solution for predicting residual disease on biopsies of breast cancer patients treated with neoadjuvant chemotherapy.

BACKGROUND: Predicting chemosensitivity before treatment could help tailor neoadjuvant chemotherapy (NAC) in early breast cancer (eBC). Pathological c...

3D tibial HU reconstruction from biplanar X-rays utilizing a hybrid PCA-CNN framework.

High-resolution Computed Tomography (CT) is the gold standard medical imaging technique for bone assessment. However, its clinical use is limited by h...

Advancements in radiation dose reduction for pediatric CT head Imaging: A scoping review of emerging Technologies, Protocols, and optimization strategies.

Computed tomography (CT) is an important imaging modality that provides cross-sectional images, aiding in the detailed visualization of internal struc...

[Chronic skin damage from UV radiation].

Ultraviolet (UV) radiation is the primary risk factor for the development of both melanocytic and nonmelanocytic skin cancer. In particular, UVA and U...