AIMC Topic: Algorithms

Clear Filters Showing 701 to 710 of 28713 articles

Enhanced image registration based brain tumour segmentation using optical particle swarm intelligence technique with Resnet Inceptionv2 HCNN.

Scientific reports
A brain tumor is the deadliest disease to cause sudden death, affecting billions of people worldwide. Artificial Intelligence (AI) powered technologies play a vital role in screening medical images to identify brain-suspecting tissue regions of attai...

Deep transfer learning based feature fusion model with Bonobo optimization algorithm for enhanced brain tumor segmentation and classification through biomedical imaging.

Scientific reports
The brain tumour (BT) is an aggressive disease among others, which leads to a very short life expectancy. Therefore, early and prompt treatment is the main stage in enhancing patients' quality of life. Biomedical imaging permits the non-invasive eval...

A proof of concept study of F-FDG PET/CT patient-level radiomics identify refractory/relapsed diffuse large B-cell lymphoma.

Scientific reports
This study aimed to evaluate diffuse large B-cell lymphoma (DLBCL) patients who have refractory/relapsed disease and characterize the heterogeneity of DLBCL using patient-level radiomics analysis based on F-FDG PET/CT. A total of 132 patients diagnos...

Automating prostate volume acquisition using abdominal ultrasound scans for prostate-specific antigen density calculations.

Scientific reports
Proposed methods for prostate cancer screening are currently prohibitively expensive (due to the high costs of imaging equipment such as magnetic resonance imaging and traditional ultrasound systems), inadequate in their detection rates, require high...

FatigueNet: A hybrid graph neural network and transformer framework for real-time multimodal fatigue detection.

Scientific reports
Fatigue creates complex challenges that present themselves through cognitive problems alongside physical impacts and emotional consequences. FatigueNet represents a modern multimodal framework that deals with two main weaknesses in present-day fatigu...

Optimizing breast cancer classification based on cat swarm-enhanced ensemble neural network approach for improved diagnosis and treatment decisions.

Scientific reports
Breast cancer remains a formidable global health challenge, emphasizing the critical importance of accurate and early diagnosis for improved patient outcomes. In recent years, machine learning, particularly deep learning, has shown substantial promis...

An intelligent community-based system for healthcare prioritisation.

Scientific reports
Healthcare rationing is unavoidable in systems constrained by limited resources. While decisions about who should be treated are ethically complex, they must reflect not only efficiency concerns but also socially accepted values. This study aims to d...

FairEduNet: a novel adversarial network for fairer educational dropout prediction.

Scientific reports
As artificial intelligence becomes increasingly prevalent in education, ensuring educational fairness has emerged as a critical concern. Algorithmic bias can lead to inequitable predictions, resulting in the unfair allocation of educational resources...

An optimized hybrid deep learning model to detect Alzheimer disease.

Scientific reports
Alzheimer's is a serious neurodegenerative disease that requires early detection for effective intervention. Traditional methods often struggle with accurately identifying the early stages, such as mild cognitive impairment (MCI), due to limitations ...

Role of human collaboration in artificial intelligence with fuzzy based mathematical models and decision making problems.

Scientific reports
The rapid development of artificial intelligence (AI) and machine learning (ML) has revolutionized computer technology, enabling it to make intelligent decisions, exhibit adaptive behavior, and foster synergistic human-AI environments. To ensure that...