AIMC Topic: Humans

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IV3TM: Inception V3 enabled bidirectional long short-term memory network for brain tumor classification.

PloS one
A brain tumor is one of the life-threatening neurological conditions affecting millions of people worldwide. Early diagnosis and classification of brain tumor types facilitate prompt treatment, thereby increasing the patient's chances of survival. Th...

MultiFAR: Multidimensional information fusion with attention-driven representation learning for student performance prediction.

PloS one
The advancement in computing technology, online learning platforms, and pedagogical tools enable educators and learners to connect without temporal and geographical boundaries. The existing deep learning models to predict student performance are eith...

Screening mild cognitive impairment using aspects of personal, social, and functional lifestyle: Machine Learning Approaches.

PloS one
OBJECTIVE: Mild cognitive impairment (MCI) signals cognitive decline beyond normal aging and increases dementia risk. Early identification enables preventative interventions, yet many patients in primary care go undetected. This study examines whethe...

Self-learning adaptive neuro-fuzzy approximation of robust control behavior in electric power steering systems.

PloS one
Data training algorithms based on Artificial Intelligence (AI) often encounter overfitting, underfitting, or bias issues. This article presents the design of a hybrid self-learning algorithm to address the above challenges. The proposed approach is d...

An efficient cyber-attack detection and classification in IoT networks with high-dimensional feature set using Levenberg-Marquardt optimized feedforward neural network.

PloS one
This paper examines the escalating challenge of detecting cyber-attacks within Internet of Things (IoT) networks, where conventional security measures often falter in addressing the speed and complexity of contemporary threats. In response to the nec...

YOLOv11-MFF: A multi-scale frequency-adaptive fusion network for enhanced CXR anomaly detection.

PloS one
Chest X-ray (CXR) represents one of the most widely utilized clinical diagnostic tools for thoracic diseases. Nevertheless, computer-aided diagnosis based on chest radiographs still faces considerable challenges in anomaly detection. Certain lesions ...

Utilizing multi-level convolutional neural networks to achieve refined modeling and visual analysis of college students' mental health data.

PloS one
Early identification of students' mental health issues has become an urgent priority in education and public health. However, existing studies often rely on questionnaire-based assessments or traditional machine learning models, which are limited by ...

MIASurviveMTP: Machine learning for immediate assessment and survival prediction after massive transfusion protocol.

PloS one
Early triage of trauma patients requiring massive transfusion (MT) may help to marshal appropriate resources and improve treatment and outcome. Artificial intelligence (AI) and machine learning (ML) offer theoretical advantages compared to convention...

Molecular Glues in Immunotherapy: Fine-Tuning Immune Responses for Precision Medicine.

International immunopharmacology
Molecular glues are a new class of tiny compounds that can rewire protein-protein interactions, providing a very selective mechanism to modify immunological signalling pathways. These substances allow immune regulators to be selectively degraded or s...

Invasive meningococcal disease in adolescents in Europe and select geographies: Disease burden, unmet medical need, and optimizing prevention.

Human vaccines & immunotherapeutics
Invasive meningococcal disease (IMD) is uncommon but serious; the case fatality rate is 8-15% and up to 20-40% of survivors experience disabling sequelae, with a substantial socioeconomic impact. Although incidence is highest in infants and young chi...