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Deep Learning Empowered Fresnel-based Lensless Fluorescence Microscopy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Miniaturized fluorescence microscopy has revolutionized the way neuroscientists study the brain in-vivo. Recent developments in computational lensless imaging promise a next generation of miniaturized microscopes in lensless fluorescence microscopy. ...

Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network.

Sensors (Basel, Switzerland)
Interpretation of neural activity in response to stimulations received from the surrounding environment is necessary to realize automatic brain decoding. Analyzing the brain recordings corresponding to visual stimulation helps to infer the effects of...

Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology cases.

Neuroradiology
PURPOSE: The noteworthy performance of Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence text generation model based on the GPT-4 architecture, has been demonstrated in various fields; however, its potential applications i...

Accuracy of ChatGPT in head and neck oncological board decisions: preliminary findings.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
OBJECTIVES: To evaluate the ChatGPT-4 performance in oncological board decisions.

Sparse convolutional neural network for high-resolution skull shape completion and shape super-resolution.

Scientific reports
Traditional convolutional neural network (CNN) methods rely on dense tensors, which makes them suboptimal for spatially sparse data. In this paper, we propose a CNN model based on sparse tensors for efficient processing of high-resolution shapes repr...

Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

Scientific reports
The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (ICU) remains challenging. Computed tomography images are still manually quantified and then underexplo...

Enhancing paranasal sinus disease detection with AutoML: efficient AI development and evaluation via magnetic resonance imaging.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Artificial intelligence (AI) in the form of automated machine learning (AutoML) offers a new potential breakthrough to overcome the barrier of entry for non-technically trained physicians. A Clinical Decision Support System (CDSS) for screen...