Physics-informed machine learning techniques have emerged to tackle challenges inherent in pure machine learning (ML) approaches. One such technique, the hybrid approach, has been introduced to estimate terrestrial evapotranspiration (ET), a crucial ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 22, 2025
Accurate organ segmentation is crucial for precise medical diagnosis. Recent methods in CNNs and Transformers have significantly enhanced automatic medical image segmentation. Their encoders and decoders often rely on simple skip connections, which f...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 22, 2025
Optical Coherence Tomography (OCT) will inevitably be contaminated by speckle noise when imaging, resulting in a decrease in the visual quality of images and affecting clinical diagnosis. Existing unsupervised denoising methods often rely on complex ...
Unsupervised image-to-image translation, which synthesizes new images from existing ones, has become a prominent research topic in computer vision. This technique is particularly valuable in the magnetic resonance (MR) imaging domain, where acquiring...
Myocardial strain plays a crucial role in diagnosing heart failure and myocardial infarction. Its computation relies on assessing heart muscle motion throughout the cardiac cycle. This assessment can be performed by following key points on each frame...
Journal of chemical information and modeling
Jul 22, 2025
Fraction unbound in plasma () is a crucial parameter in physiologically based toxicokinetic (PBTK) models, representing the fraction of a chemical compound that is not sequestered by plasma proteins when present in the bloodstream. This is often used...
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...
This study presents a deep learning framework for the non-destructive assessment of lipid oxidation in salmon flesh, quantified by thiobarbituric acid reactive substances (TBARS), under diverse storage conditions (-20, 0, 4, 20 °C, and dynamic temper...
The accumulation of organic pollutants in the environment has significantly impacted the lives of flora and fauna, resulting in disruptions in the biological ecosystem. Carcinogenicity has been one of the most alarming adverse effects exhibited by th...
In this study, we introduce a novel encoding algorithm utilizing contrastive learning to address the substantial data size challenges inherent in mass spectrometry imaging. Our algorithm compresses MSI data into fixed-length vectors, significantly re...
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