AIMC Topic: Neural Networks, Computer

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Optimization enabled ensemble based deep learning model for elderly falling risk prediction.

Computer methods in biomechanics and biomedical engineering
Predicting fall risk in the elderly is crucial for enhancing safety and well-being. Aging and chronic diseases often impair balance, increasing fall risk. This study aims to develop an advanced fall risk prediction model using an optimized deep learn...

Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

Computers in biology and medicine
In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately predicting and early response to lymphoma treatment will be useful for initiating treatment plans to achieve a greater rate of cure or reduced risk of tre...

A comparative analysis of metamodels for 0D cardiovascular models, and pipeline for sensitivity analysis, parameter estimation, and uncertainty quantification.

Computers in biology and medicine
Zero-dimensional (0D) cardiovascular models are reduced-order models aimed at studying the global dynamics of the whole circulation system or transport within it. They are employed to obtain estimates of important biomarkers for surgery planning and ...

Radiology report generation based on adaptive enhanced fusion of multi features.

Computers in biology and medicine
The radiology report is essential for doctors' diagnosis and treatment. The automatic generation of radiology reports can assist doctors in diagnosis and treatment, thereby reducing their workload. Some existing studies consider the entire radiologic...

Multimodal AI framework for lung cancer diagnosis: Integrating CNN and ANN models for imaging and clinical data analysis.

Computers in biology and medicine
Lung cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the critical need for accurate and early diagnostic solutions. This study introduces a novel multimodal artificial intelligence (AI) framework that integrates Conv...

Multiclass ensemble framework for enhanced prostate gland Segmentation: Integrating Self-ONN decoders with EfficientNet.

Computers in biology and medicine
Digital pathology relies on the morphological architecture of prostate glands to recognize cancerous tissue. Prostate cancer (PCa) originates in walnut shaped prostate gland in the male reproductive system. Deep learning (DL) pipelines can assist in ...

Short-term spatial prediction of algal blooms in Lake Taihu via machine learning and GOCI observations.

Journal of environmental management
Harmful algal blooms are critical issues in eutrophic lakes worldwide. However, predicting the spatial distribution of algal blooms at the pixel level is still a challenge. In this study, floating algae cover (FAC) was used to extract algal coverage ...

Automated 3D facial smile attractiveness assessment before and after orthognathic surgery using transfer learning: A preliminary study.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
The aesthetic appearance of the mouth during smiling significantly influences facial attractiveness, thereby, making smile analysis crucial in orthodontics, craniofacial surgery, and cosmetic dentistry. Accurate and quantitative evaluation of facial ...

Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations.

Toxicological sciences : an official journal of the Society of Toxicology
Transcriptomic analyses have been an effective approach to investigate the biological responses and metabolic perturbations by environmental contaminants in rodent models. However, it is well recognized that metabolic networks are highly connected an...

Automatic adult age estimation using bone mineral density of proximal femur via deep learning.

Forensic science international
Accurate adult age estimation (AAE) is critical for forensic and anthropological applications, yet traditional methods relying on bone mineral density (BMD) face significant challenges due to biological variability and methodological limitations. Thi...