AIMC Topic: Deep Learning

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The combination of HSI and NMR techniques with deep learning for identification of geographical origin and GI markers of Lycium barbarum L.

Food chemistry
Lycium barbarum L. (L. barbarum) is renowned worldwide for its nutritional and medicinal benefits. Rapid and accurate identification of L.barbarum's geographic origin is essential because its nutritional content, medicinal efficacy, and market price ...

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

Interdisciplinary sciences, computational life sciences
The kidney is an abdominal organ in the human body that supports filtering excess water and waste from the blood. Kidney diseases generally occur due to changes in certain supplements, medical conditions, obesity, and diet, which causes kidney functi...

Enhancing diagnosis: ensemble deep-learning model for fracture detection using X-ray images.

Clinical radiology
AIM: Orthopedic trauma results in the injury of bone joints and tendons of the body. A radiologist reviews and monitors large numbers of radiographs daily, which can lead to the diagnostic error. Therefore, there is a need to automate the detection o...

Human hand gesture recognition using fast Fourier transform with coot optimization based on deep neural network.

Network (Bristol, England)
Hand motion detection is particularly important for managing the movement of individuals who have limbs amputated. The existing algorithm is complex, time-consuming and difficult to achieve better accuracy. A DNN is suggested to recognize human hand ...

Multimodal Artificial Intelligence in Medicine.

Kidney360
Traditional medical artificial intelligence models that are approved for clinical use restrict themselves to single-modal data ( e.g ., images only), limiting their applicability in the complex, multimodal environment of medical diagnosis and treatme...

Enhanced IDOL segmentation framework using personalized hyperspace learning IDOL.

Medical physics
BACKGROUND: Adaptive radiotherapy (ART) workflows have been increasingly adopted to achieve dose escalation and tissue sparing under shifting anatomic conditions, but the necessity of recontouring and the associated time burden hinders a real-time or...

Hybrid optimal feature selection-based iterative deep convolution learning for COVID-19 classification system.

Computers in biology and medicine
The COVID-19 pandemic has necessitated the development of innovative and efficient methods for early detection and diagnosis. Integrating Internet of Things (IoT) devices and applications in healthcare has facilitated various functions. This work aim...

Deep Learning Powers Protein Identification from Precursor MS Information.

Journal of proteome research
Proteome analysis currently heavily relies on tandem mass spectrometry (MS/MS), which does not fully utilize MS1 features, as many precursors remain unselected for MS/MS fragmentation, especially in the cases of low abundance samples and wide abundan...

AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrument...