Discover deep learning: advanced neural networks, AI applications, and the key role this technology will play in the future of innovation.
Accurate instance segmentation of teeth in panoramic dental X-rays is a challenging task due to variations in tooth morphology and overlapping regions. In this study, we propose a new algorithm, for instance, segmentation of the different teeth in panoramic dental X-rays.
Evidence is rapidly accumulating that multifactorial nocturnal monitoring, through the coupling of wearable devices and deep learning, may be disruptive for early diagnosis and assessment of sleep disorders.
Parkinson’s Disease (PD) is one of the most common non-curable neurodegenerative diseases. Diagnosis is achieved clinically on the basis of different symptoms with considerable delays from the onset of neurodegenerative processes in the central nervous system.
Recent advances in single-cell RNA-sequencing in order to study cells in biology, and the increasing amount of data available, led to the development of algorithms for analyzing single cells from gene expression data.
The paper presents a comparative analysis of three distinct approaches based on deep learning for COVID-19 detection in chest CTs.
As we announced a few weeks ago, the launch of MS humanAId by Emme Esse has seen synbrAIn's active involvement in developing a system that leverages artificial intelligence to support diagnostic image analysis. Specifically, the development of the AID CHEST XR PNEUMO module…
Glioma is a type of heterogeneous tumor originating in the brain, characterized by the coexistence of multiple subregions with different phenotypic characteristics, which further determine heterogeneous profiles, likely to respond variably to treatment. Identifying spatial variations of gliomas is necessary for targeted therapy.
ImageCLEF is an international initiative organized by the CLEF initiative lab, aimed at fostering the development of new AI and machine learning-based solutions to address challenges in the healthcare and medical domains. This year’s edition focused on developing the best possible solution for…
The paper presents and comparatively analyses several deep learning approaches to automatically detect tuberculosis related lesions in lung CTs, in the context of the ImageClef 2020 Tuberculosis task.
