AIMC Topic: Deep Learning

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Diagnostic support in pediatric craniopharyngioma using deep learning.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
PURPOSE: We studied a pediatric group of patients with sellar-suprasellar tumors, aiming to develop a convolutional deep learning algorithm for radiological assistance to classify them into their respective cohort.

Virtual reality-empowered deep-learning analysis of brain cells.

Nature methods
Automated detection of specific cells in three-dimensional datasets such as whole-brain light-sheet image stacks is challenging. Here, we present DELiVR, a virtual reality-trained deep-learning pipeline for detecting c-Fos cells as markers for neuron...

Advancing musculoskeletal tumor diagnosis: Automated segmentation and predictive classification using deep learning and radiomics.

Computers in biology and medicine
OBJECTIVES: Musculoskeletal (MSK) tumors, given their high mortality rate and heterogeneity, necessitate precise examination and diagnosis to guide clinical treatment effectively. Magnetic resonance imaging (MRI) is pivotal in detecting MSK tumors, a...

Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles.

Computers in biology and medicine
Distant metastasis of cancer is a significant contributor to cancer-related complications, and early identification of unidentified stomach adenocarcinoma is crucial for a positive prognosis. Changes inDNA methylation are being increasingly recognize...

RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic registration of differently stained whole slide images (WSIs) is crucial for improving diagnosis and prognosis by fusing complementary information emerging from different visible structures. It is also useful t...

DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

Journal of chemical information and modeling
It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary ...

A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).

Prototype Learning for Medical Time Series Classification via Human-Machine Collaboration.

Sensors (Basel, Switzerland)
Deep neural networks must address the dual challenge of delivering high-accuracy predictions and providing user-friendly explanations. While deep models are widely used in the field of time series modeling, deciphering the core principles that govern...

Revealing the mechanisms of semantic satiation with deep learning models.

Communications biology
The phenomenon of semantic satiation, which refers to the loss of meaning of a word or phrase after being repeated many times, is a well-known psychological phenomenon. However, the microscopic neural computational principles responsible for these me...

External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease.

Scientific reports
A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for au...