Cardiovascular

Survival prediction of colorectal cancer using 101 machine learning methods based on immune-related genes: A machine learning study.

Colorectal cancer (CRC) is characterized by high incidence and mortality rates. Early identification of high-risk CRC patients and timely intervention are crucial for reducing mortality rates. This study aims to develop a prognostic model incorporating immune-related genes using 101 machine learning algorithms. We utilized data from 630 CRC patients in The Cancer Genome Atlas Program database and ...

Longitudinal Plasma Proteomics Reveals an Immuno-thrombotic Signature that Predicts Radiation Pneumonitis in Lung Cancer.

PURPOSE: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy, often poorly predicted by static clinical and dosimetric models. We aimed to identify a robust, blood-based proteomic signature grounded in the longitudinal biological response to radiation to enable accurate, early risk stratification. EXPERIMENTAL DESIGN: We conducted a prospective study using high-throu...

Generating synthetic CT from MR images for radiation-free computer-assisted quantification of hip morphology.

OBJECTIVES: To compare MR image-based synthetic CT (sCT) with conventional CT for computer-assisted quantification of hip morphology by evaluating oss...

U-CBAMNet: an attention-guided deep learning model for accurate and explainable prediction of HER2 expression from breast ultrasound cine videos.

BACKGROUND: Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression is essential for guiding targeted therapy in breast canc...

Single-cell N4-acetylcytidine regulatory landscape identifies ARIH1 as a ferroptosis-suppressive oncogenic driver in lung adenocarcinoma.

BACKGROUND: N4-acetylcytidine (ac4C) is an emerging post-transcriptional RNA modification implicated in cancer biology, yet its cellular distribution,...

Optimizing breast core needle biopsy biomarker throughput using an AI-based workflow.

AIMS: To evaluate the feasibility, appropriate relevance and impact on turnaround time (TAT) of an AI-supported workflow in which AI, integrated in th...

Generalizability of an AI-based mammogram risk score (MRS) for breast cancer among diverse populations of women.

Conventional prediction models incorporating genetic and clinical factors including breast density underperform in non-European populations. We invest...

Tumor-preserving Deformable Registration of Longitudinal Breast DCE MRI during Neoadjuvant Chemotherapy.

Purpose To develop a deep learning-based deformable registration method for breast dynamic contrast-enhanced (DCE) MRI that preserves tumor regions wh...

PFAS is associated with perineural invasion in triple-negative breast cancer with a potential role for Cathepsin D dysregulation: a multi-omics and experimental study.

Per- and polyfluoroalkyl substances (PFAS) are persistent pollutants linked to breast cancer (BC), but their role in perineural invasion (PNI) of trip...

Interpretable machine learning models for bladder cancer overall survival prediction development and external validation via SEER database and Chinese cohort analysis.

OBJECTIVE: We developed interpretable machine learning(ML) models to predict overall survival in bladder cancer patients. This approach aims to improv...

RADIANT: A fully configurable radiotherapy dose prediction framework.

Treatment planning is a multi-disciplinary effort that requires medical decision-making, specialized training, and access to specialized software. Rec...

A neural network embedding the linear-quadratic model for improved prediction of cellular response to ion beam exposure.

Predicting biological responses to ionizing radiation is challenging due to the complex, multi-scale mechanisms involved. Traditional machine learning...

Clinical knowledge constrained multi-task learning framework for breast cancer diagnosis using ultrasound videos.

Ultrasound is widely used in breast cancer diagnosis due to its cost-effectiveness, non-invasiveness, and radiation-free properties. Computer-aided di...

Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.

BACKGROUND: Accurate and timely disease detection is essential in modern healthcare. Conventional imaging methods such as computed tomography (CT), ma...

Artificial intelligence classification of spatial CD8 + T-cell distribution on computed tomography in oropharyngeal cancer.

CD8 + T-cell presence and distribution in oropharyngeal cancer (OPC) reflects specific immune phenotypes and are linked to prognosis. Image processing...

Unraveling the Multifunctional and Translational Paradigm of Nanoparticulate Systems against Colorectal Cancer.

Colorectal cancer (CRC) is a health burden due to its high mortality rate, recurrence rate, and drug resistance. The limitations of traditional method...

Advanced Data Analytics and Machine Learning for Geospatial Interpolation, Anomaly Detection, Background Prediction and Emergency Evacuation Routing in Real-Time Radiation Monitoring System.

For identifying natural trends, hotspots, hazardous areas, and mitigating potential health risk to the public and environment, spatial analysis of rad...

An interpretable machine learning model integrating [18F]FDG PET/CT radiomics and clinical features for predicting perforation following chemotherapy in gastrointestinal lymphoma: a multicenter study.

BACKGROUND: Perforation following chemotherapy in gastrointestinal lymphoma (PFCGL) is a rare but severe and life-threatening complication. Early pre-...

Artificial Intelligence for Molecular Subtyping in Unresectable Gallbladder Cancer: A Proof-of-Concept Study for CT-based HER2 Status Prediction.

BACKGROUND/AIMS: Human epidermal growth factor receptor 2 (HER2) overexpression is a critical therapeutic target in gallbladder cancer (GBC), but dete...

Artificial intelligence integrated multi-omics and multimodal studies promote the efficacy of neoadjuvant chemotherapy in breast cancer: opportunities, challenges, and future perspectives.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is a critical therapeutic strategy for locally advanced breast cancer; however, its clinical utility is con...