AIMC Topic: Humans

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A comprehensive approach to anticipating the progression of mild cognitive impairment.

Brain research
The immersive experience provided by our approach empowers researchers with an intuitive exploration of brain structures. Within the brain's central nervous system, encompassing both white and gray matter, symptoms associated with Alzheimer's disease...

Leveraging Artificial Intelligence to Reduce Neuroscience ICU Length of Stay.

Journal of healthcare management / American College of Healthcare Executives
GOAL: Efficient patient flow is critical at Tampa General Hospital (TGH), a large academic tertiary care center and safety net hospital with more than 50,000 discharges and 30,000 surgical procedures per year. TGH collaborated with GE HealthCare Comm...

AI integrations with lung cancer screening: Considerations in developing AI in a public health setting.

European journal of cancer (Oxford, England : 1990)
Lung cancer screening implementation has led to expanded imaging of the chest in older, tobacco-exposed populations. Growing numbers of screening cases are also found to have CT-detectable emphysema or elevated levels of coronary calcium, indicating ...

AI-based association analysis for medical imaging using latent-space geometric confounder correction.

Medical image analysis
This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves confounding by removing confounder-related information from latent rep...

A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection.

Computers in biology and medicine
Cancer is a severe threat to public health. Early diagnosis of disease is critical, but the lack of experts in this field, the personal assessment process, the clinical workload, and the high level of similarity in disease classes make it difficult. ...

GLEAM: A multimodal deep learning framework for chronic lower back pain detection using EEG and sEMG signals.

Computers in biology and medicine
Low Back Pain (LBP) is the most prevalent musculoskeletal condition worldwide and a leading cause of disability, significantly affecting mobility, work productivity, and overall quality of life. Due to its high prevalence and substantial economic bur...

An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives.

Computers in biology and medicine
UNLABELLED: Infectious diseases, including tuberculosis (TB), HIV/AIDS, and emerging pathogens like COVID-19 pose severe global health challenges due to their rapid spread and significant morbidity and mortality rates. Next-generation sequencing (NGS...

Classification method for nailfold capillary images using an optimized sugeno fuzzy ensemble of convolutional neural networks.

Computers in biology and medicine
This study developed a novel binary classification method for analyzing nailfold capillary images associated with the risk of developing sclerosis. The proposed approach combined a Sugeno fuzzy integral inference system with an ensemble of convolutio...

FFSWOAFuse: Multi-modal medical image fusion via fermatean fuzzy set and whale optimization algorithm.

Computers in biology and medicine
Multi-modal medical image fusion (MMIF) plays a crucial role in obtaining valuable and significant information from different medical modalities. This process has generated a single resultant image that is suitable for better clinical assessments and...

Accurate phenotyping of luminal A breast cancer in magnetic resonance imaging: A new 3D CNN approach.

Computers in biology and medicine
Breast cancer (BC) remains a predominant and deadly cancer in women worldwide. By 2040, projections indicate that more than 3 million new cases of breast cancer will emerge annually, culminating in more than 1 million deaths worldwide. Early detectio...