AIMC Topic: Deep Learning

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Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of i...

A deep learning anthropomorphic model observer for a detection task in PET.

Medical physics
BACKGROUND: Lesion detection is one of the most important clinical tasks in positron emission tomography (PET) for oncology. An anthropomorphic model observer (MO) designed to replicate human observers (HOs) in a detection task is an important tool f...

Self-adaptive deep learning-based segmentation for universal and functional clinical and preclinical CT image analysis.

Computers in biology and medicine
BACKGROUND: Methods to monitor cardiac functioning non-invasively can accelerate preclinical and clinical research into novel treatment options for heart failure. However, manual image analysis of cardiac substructures is resource-intensive and error...

Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review.

Journal francais d'ophtalmologie
In the last decade, artificial intelligence (AI) has significantly impacted ophthalmology, particularly in managing corneal diseases, a major reversible cause of blindness. This review explores AI's transformative role in the corneal subspecialty, wh...

Deep Learning Enabled Universal Multiplexed Fluorescence Detection for Point-of-Care Applications.

ACS sensors
There is a significant demand for multiplexed fluorescence sensing and detection across a range of applications. Yet, the development of portable and compact multiplexable systems remains a substantial challenge. This difficulty largely stems from th...

Versatile Deep Learning Pipeline for Transferable Chemical Data Extraction.

Journal of chemical information and modeling
Chemical information disseminated in scientific documents offers an untapped potential for deep learning-assisted insights and breakthroughs. Automated extraction efforts have shifted from resource-intensive manual extraction toward applying machine ...

3DReact: Geometric Deep Learning for Chemical Reactions.

Journal of chemical information and modeling
Geometric deep learning models, which incorporate the relevant molecular symmetries within the neural network architecture, have considerably improved the accuracy and data efficiency of predictions of molecular properties. Building on this success, ...

Accuracy of automated forensic dental age estimation lab (F-DentEst Lab) on large Malaysian dataset.

Forensic science international
When a disaster occurs, the authority must prioritise two things. First, the search and rescue of lives, and second, the identification and management of deceased individuals. However, with thousands of dead bodies to be individually identified in ma...

Assessment of image quality and diagnostic accuracy for cervical spondylosis using T2w-STIR sequence with a deep learning-based reconstruction approach.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
OBJECTIVES: To investigate potential of enhancing image quality, maintaining interobserver consensus, and elevating disease diagnostic efficacy through the implementation of deep learning-based reconstruction (DLR) processing in 3.0 T cervical spine ...