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Synthetic Technology Blog of NeuroBot
AI generative data synthesis is widely applied across various industries. Learn from classic use cases, identify relevant application scenarios, and accelerate your project progress.
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Healthcare
Generative Artificial Intelligence: Synthetic Datasets in Dentistry
Generative AI creates synthetic dental datasets, improving model fairness, privacy, and diagnostic accuracy in dentistry.
Latest posts
Generative Artificial Intelligence: Synthetic Datasets in Dentistry
Generative AI creates synthetic dental datasets, improving model fairness, privacy, and diagnostic accuracy in dentistry.
Generative Models Improve Fairness of Medical Classifiers Under Distribution Shifts
By generating synthetic image samples specific to underrepresented groups, diffusion models help medical imageclassifiers to achieve greater fairness metrics across a variety of medical disciplines and demographic attributes.
Enhancing Waterbody Detection with Synthetic Datasets: Overcoming Out-of-Distribution Challenges
This study explores using synthetic datasets and deep learning to improve waterbody detection and segmentation in diverse environments.
Advancing Retinal Disease Diagnosis: Deep Learning for Non-Perfusion Area Segmentation in Fundus and AI-Generated Fluorescein Angiography
This study explores using deep learning and AI-generated fluorescein angiography for non-invasive, accurate retinal disease diagnosis.
Advancing Organ Toxicity Assessment with Generative AI: A New Era in Drug Safety
This study explores using generative AI and organ transcriptomics to predict multi-organ toxicity, enhancing drug safety assessments.
Revolutionizing Pharmaceutical Formulation: In Silico Optimization and Particle Engineering Using Generative AI
This study explores using generative AI for in silico pharmaceutical formulation optimization, improving efficiency, cost, and drug quality.
Revolutionizing Material Design: Nature-Inspired Architected Materials Using Unsupervised Deep Learning
This study explores using unsupervised deep learning to design nature-inspired architected materials with optimized properties for various applications.
Enhancing X-Ray Bone Segmentation with Adversarial Robustness and Synthetic Data
This study explores using synthetic data and adversarial training to improve X-ray bone segmentation accuracy and robustness.
Transforming Construction with Generative Decision Support: The Role of Field Information Modeling (FIM)
This study explores using the FIM framework for generative decision support in construction, optimizing design, efficiency, and sustainability.