IEEE transactions on bio-medical engineering
Sep 1, 2025
OBJECTIVE: Predicting normative pediatric growth is crucial to identify developmental anomalies. While traditional statistical and computational methods have shown promising results predicting personalized development, they either rely on statistical...
Cyanobacterial blooms pose significant environmental and public health risks due to the production of toxins that contaminate water sources and disrupt aquatic ecosystems. Rapid and accurate identification of cyanobacterial species is crucial for eff...
IEEE transactions on bio-medical engineering
Sep 1, 2025
In multispectral fluorescence lifetime imaging (FLIm), achieving consistent imaging quality across all spectral channels is crucial for accurately identifying a wide range of fluorophores. However, these essential measurements are frequently compromi...
IEEE transactions on bio-medical engineering
Sep 1, 2025
This study investigates a novel approach for analyzing Sit-to-Stand (STS) movements using millimeter-wave (mmWave) radar technology, aiming to develop a non-contact, privacy-preserving, and all-day operational solution for healthcare applications. A ...
IEEE transactions on visualization and computer graphics
Sep 1, 2025
Geometry- and appearance-controlled full-body human image generation is an interesting but challenging task. Existing solutions are either unconditional or dependent on coarse conditions (e.g., pose, text), thus lacking explicit geometry and appearan...
International journal of computerized dentistry
Sep 1, 2025
AIM: Malocclusion has emerged as a burgeoning global public health concern. Individuals with an anterior crossbite face an elevated risk of exhibiting characteristics such as a concave facial profile, negative overjet, and poor masticatory efficiency...
Journal of the science of food and agriculture
Aug 30, 2025
BACKGROUND: The flavor profile and product quality of white tea, heavily dependent on its place of origin, significantly influence consumers' purchasing decisions. Quantitative adulteration testing for tea origin has encountered challenges due to the...
Circulation journal : official journal of the Japanese Circulation Society
Aug 25, 2025
BACKGROUND: The aim of this study was to retrain our existing deep learning-based fully automated aortic valve leaflets/root measurement algorithm, using computed tomography (CT) data for root dilatation (RD), and assess its clinical feasibility.
AIMS: Our aim is to develop a deep learning-based system for automatically identifying and classifying benign and malignant tumours of the eyelid to improve diagnostic accuracy and efficiency.
AIMS: To investigate rule-based and deep learning (DL)-based methods for the automatically generating natural language diagnostic reports for macular diseases.
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