AIMC Topic: Neural Networks, Computer

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Molecular property prediction based on graph structure learning.

Bioinformatics (Oxford, England)
MOTIVATION: Molecular property prediction (MPP) is a fundamental but challenging task in the computer-aided drug discovery process. More and more recent works employ different graph-based models for MPP, which have achieved considerable progress in i...

DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm.

Bioinformatics (Oxford, England)
MOTIVATION: Despite the extensive manufacturing of antiviral drugs and vaccination, viral infections continue to be a major human ailment. Antiviral peptides (AVPs) have emerged as potential candidates in the pursuit of novel antiviral drugs. These p...

Application of deep learning to pressure injury staging.

Journal of wound care
OBJECTIVE: Accurate assessment of pressure injuries (PIs) is necessary for a good outcome. Junior and non-specialist nurses have less experience with PIs and lack clinical practice, and so have difficulty staging them accurately. In this work, a deep...

UTILIZATION OF ARTIFICIAL INTELLIGENCE FOR PREDICTIVE MODELING IN DENTAL IMPLANTOLOGY.

Georgian medical news
Artificial intelligence (AI) is making waves in dentistry, with applications in predicting dental implant success. AI models analyze patient data (X-rays, medical history) to identify factors influencing implant viability. The aim is to identify exis...

Role of artificial intelligence in multiple sclerosis management.

European review for medical and pharmacological sciences
From a clinical viewpoint, there are enormous obstacles to early detection and diagnosis as well as treatment interventions for multiple sclerosis (MS). With the growing application of methods based on artificial intelligence (AI) to medical problems...

Convolutional Neural Network-Based Prediction of Axial Length Using Color Fundus Photography.

Translational vision science & technology
PURPOSE: To develop convolutional neural network (CNN)-based models for predicting the axial length (AL) using color fundus photography (CFP) and explore associated clinical and structural characteristics.

Prediction of prognosis using artificial intelligence-based histopathological image analysis in patients with soft tissue sarcomas.

Cancer medicine
BACKGROUND: Prompt histopathological diagnosis with accuracy is required for soft tissue sarcomas (STSs) which are still challenging. In addition, the advances in artificial intelligence (AI) along with the development of pathology slides digitizatio...

Comprehensive analysis of clinical images contributions for melanoma classification using convolutional neural networks.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Timely diagnosis plays a critical role in determining melanoma prognosis, prompting the development of deep learning models to aid clinicians. Questions persist regarding the efficacy of clinical images alone or in conjunction with dermos...

Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.

Translational vision science & technology
PURPOSE: Multiple clinical visits are necessary to determine progression of keratoconus before offering corneal cross-linking. The purpose of this study was to develop a neural network that can potentially predict progression during the initial visit...

Machine learning and deep learning to identifying subarachnoid haemorrhage macrophage-associated biomarkers by bulk and single-cell sequencing.

Journal of cellular and molecular medicine
We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single-cell transcript...