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Diffusion-based image translation model from low-dose chest CT to calcium scoring CT with random point sampling.

Computers in biology and medicine
BACKGROUND: Coronary artery calcium (CAC) scoring is an important method for cardiovascular risk assessment. While artificial intelligence (AI) has been applied to automate CAC scoring in calcium scoring computed tomography (CSCT), its application to...

Screening of bioactive compounds and deep learning-driven quality control of Angong Niuhuang pills.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Angong Niuhuang Pills (AGNHP), a famous Chinese medicine compound preparation, is widely used to treat stroke and other brain disorders. However, owing to the complexity of herbal components and diversity of production...

Contribution of Labrum and Cartilage to Joint Surface in Different Hip Deformities: An Automatic Deep Learning-Based 3-Dimensional Magnetic Resonance Imaging Analysis.

The American journal of sports medicine
BACKGROUND: Multiple 2-dimensional magnetic resonance imaging (MRI) studies have indicated that the size of the labrum adjusts in response to altered joint loading. In patients with hip dysplasia, it tends to increase as a compensatory mechanism for ...

Post-processing steps improve generalisability and robustness of an MRI-based radiogenomic model for human papillomavirus status prediction in oropharyngeal cancer.

European radiology
OBJECTIVES: To assess the impact of image post-processing steps on the generalisability of MRI-based radiogenomic models. Using a human papillomavirus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC) prediction model, this study examines...

Undergraduate Nursing Students' Perspectives on Artificial Intelligence in Academia.

The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres
With Artificial Intelligence (AI) tools becoming increasingly commonplace, the usage of AI-enabled tools in education has also grown. AI-enabled tools refer to machines incorporated with human-like capabilities, such as reasoning, interpretation, and...

AI-guided spatiotemporal dispersion mapping for individualized ablation in an all-comer cohort with atrial fibrillation.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
BACKGROUND: Artificial intelligence (AI)-guided spatiotemporal dispersion (stD) mapping has been shown to improve outcomes in patients with persistent atrial fibrillation (AF). However, the relationship between stD mapping and markers of atrial cardi...

Dual energy CT-based Radiomics for identification of myocardial focal scar and artificial beam-hardening.

International journal of cardiology
BACKGROUND: Computed tomography is an inadequate method for detecting myocardial focal scar (MFS) due to its moderate density resolution, which is insufficient for distinguishing MFS from artificial beam-hardening (BH). Virtual monochromatic images (...

Plasma proteomic profiles for early detection and risk stratification of non-small cell lung carcinoma: A prospective cohort study with 52,913 participants.

International journal of cancer
Early detection of non-small cell lung cancer (NSCLC) can improve survival rates, and plasma proteomics may provide effective tools for risk prediction. The population for this study included 52,913 participants and 2911 plasma proteomics from UK Bio...

An EEG-based imagined speech recognition using CSP-TP feature fusion for enhanced BCI communication.

Behavioural brain research
BACKGROUND: Imagined speech has emerged as a promising paradigm for intuitive control of brain-computer interface (BCI)-based communication systems, providing a means of communication for individuals with severe brain disabilities. In this work, a no...

Assessing the readiness of dental electronic health records for machine learning prediction of procedure outcomes: Insights from the bigmouth repository on composite and amalgam restoration survival rates.

Journal of dentistry
OBJECTIVE: Dental electronic health records (EHRs) often lack comprehensive data for evaluating procedure outcomes. Machine learning (ML) enables predictive modeling but its applicability to dental EHR data remains unclear. This study assessed the re...