AIMC Topic: Neural Networks, Computer

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Machine Learning-Aided Optimization of In Vitro Tetraploid Induction in Cannabis.

International journal of molecular sciences
Polyploidy, characterized by an increase in the number of whole sets of chromosomes in an organism, offers a promising avenue for cannabis improvement. Polyploid cannabis plants often exhibit altered morphological, physiological, and biochemical char...

Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for precise treatment planning. This study aims to utilize convolutional neural networks based on dual-time-point F-FDG PET/CT to predict the malignant ris...

Deep learning-based automated guide for defining a standard imaging plane for developmental dysplasia of the hip screening using ultrasonography: a retrospective imaging analysis.

BMC medical informatics and decision making
BACKGROUND: We aimed to propose a deep-learning neural network model for automatically detecting five landmarks during a two-dimensional (2D) ultrasonography (US) scan to develop a standard plane for developmental dysplasia of the hip (DDH) screening...

Sway frequencies may predict postural instability in Parkinson's disease: a novel convolutional neural network approach.

Journal of neuroengineering and rehabilitation
BACKGROUND: Postural instability greatly reduces quality of life in people with Parkinson's disease (PD). Early and objective detection of postural impairments is crucial to facilitate interventions. Our aim was to use a convolutional neural network ...

Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch.

Scientific reports
The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) mismatch holds potential value in identifying candidates for recanalization treatment. However, the visual assessment of DWI-FLAIR mismatch is subject to l...

HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification.

Scientific reports
Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventional CNN-based models face limitations such as high computational overhead, noise sensitivity, and data imbalance. This paper introduces HDL-ACO, a nov...

Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.

Scientific reports
Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of colorectal diseases, there remains a large gap between the current state of CCE in clinical practice, and the state of its counterpart optical colonosc...

A web-based artificial intelligence system for label-free virus classification and detection of cytopathic effects.

Scientific reports
Identifying viral replication within cells demands labor-intensive isolation methods, requiring specialized personnel and additional confirmatory tests. To facilitate this process, we developed an AI-powered automated system called AI Recognition of ...

Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data.

Scientific reports
A brain tumor is an abnormal growth of cells within the brain or surrounding tissues, which can be either benign or malignant. Brain tumors develop in various regions of the brain, each affecting different functions such as movement, speech, and visi...

Capsule network-based deep learning for early and accurate diabetic retinopathy detection.

International ophthalmology
Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition in healthcare in view of its diagnostic difficulties. Past approaches are based on assessment of the fundus images and the size of the cup and the dis...