AIMC Topic: Neural Networks, Computer

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Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.

Tomography (Ann Arbor, Mich.)
According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people's lives, particularly c...

Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction.

BMC medical informatics and decision making
BACKGROUND: Differentiated thyroid cancer (DTC) is a common endocrine malignancy with rising incidence and frequent recurrence, despite a generally favorable prognosis. Accurate recurrence prediction is critical for guiding post-treatment strategies....

A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases.

Scientific reports
Modern agriculture increasingly relies on technologies that enhance farmers' efficiency and economic growth. One challenge is the accurate identification of disease-affected plants, whose characteristics like structure, size, texture, and color can v...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Scientific reports
Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disorders early is essential for effective treatment, which traditionally relies on polysomnogram (PSG) t...

Dual level dengue diagnosis using lightweight multilayer perceptron with XAI in fog computing environment and rule based inference.

Scientific reports
Over the last fifty years, arboviral infections have made an unparalleled contribution to worldwide disability and morbidity. Globalization, population growth, and unplanned urbanization are the main causes. Dengue is regarded as the most significant...

Constructing a prediction model for acute pancreatitis severity based on liquid neural network.

Scientific reports
Acute pancreatitis (AP) is a common disease, and severe acute pancreatitis (SAP) has a high morbidity and mortality rate. Early recognition of SAP is crucial for prognosis. This study aimed to develop a novel liquid neural network (LNN) model for pre...

An intelligent optimized object detection system for disabled people using advanced deep learning models with optimization algorithm.

Scientific reports
Visually impaired persons face several problems in their day-to-day lives, and technological intermediaries might help them encounter their challenges. Among other beneficial technologies, object detection (OD) is a computer technology related to ima...

Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition.

eLife
Traditional models of reading lack a realistic simulation of the early visual processing stages, taking input in the form of letter banks and predefined line segments, making them unsuitable for modeling early brain responses. We used variations of t...

Machine Learning-Assisted Molecular Structure Embedding for Accurate Prediction of Emerging Contaminant Removal by Ozonation Oxidation.

Environmental science & technology
Ozone has demonstrated high efficacy in depredating emerging contaminants (ECs) during drinking water treatment. However, traditional quantitative structure-activation relationship (QSAR) models often fall short in effectively normalizing and charact...

An automated cascade framework for glioma prognosis via segmentation, multi-feature fusion and classification techniques.

Biomedical physics & engineering express
Glioma is one of the most lethal types of brain tumors, accounting for approximately 33% of all diagnosed brain tumor cases. Accurate segmentation and classification are crucial for precise glioma characterization, emphasizing early detection of mali...