AIMC Topic: Humans

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A deep learning framework with hybrid stacked sparse autoencoder for type 2 diabetes prediction.

Scientific reports
Sparse numerical datasets are dominant in fields such as applied mathematics, astronomy, finance, and healthcare, presenting challenges due to their high dimensionality and sparse distribution. The predominance of zero values complicates optimal feat...

Visuospatial performance and its neural substrates in Dementia with Lewy Bodies during a pointing task.

Scientific reports
Dementia with Lewy Bodies (DLB) is characterized by motor and cognitive deficits that often overlap with other neurodegenerative disorders, complicating its diagnosis. This study combined linear mixed-effects modeling and machine learning to investig...

Enhancing indoor monitoring of visually impaired people using temporal convolutional network with optimization model in IoT environment.

Scientific reports
The Internet of Things (IoT) has emerged as a powerful technology in various fields, including healthcare, assisting the elderly and disabled individuals. Solution-based IoT is widely utilized in healthcare support in diverse aspects of their daily l...

Advancements in fusion-based deep representation learning for enhanced cervical precancerous lesion classification using biomedical image analysis.

Scientific reports
One such prevalent kind of cancer among women is cervical cancer (CC). Fatality rates and incidence are progressively increasing, mainly in developing countries, due to a lack of experienced specialists, inadequate public awareness, and limited scree...

Multidimensional factors of health-related quality of life in parkinson's disease using ensemble learning and network analysis.

Scientific reports
Parkinson's disease (PD) causes motor, non-motor, and mental health challenges that significantly impact health-related quality of life (HRQoL); however, previous studies relied on subjective assessments. Several factors are associated with poor HRQo...

Isometric representations in neural networks improve robustness.

Scientific reports
Artificial and biological agents are unable to learn given completely random and unstructured data. The structure of data is encoded in the distance or similarity relationships between data points. In the context of neural networks, the neuronal acti...

Psychometric evaluation of an instrument measuring artificial intelligence utilization in decision-making domains of healthcare organizations.

Scientific reports
The decision-making process in healthcare services encounters numerous challenges. Artificial intelligence (AI) has significantly contributed to enhancing healthcare decision-making. There is a lack of validated instruments available in the literatur...

Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile.

Scientific reports
Soft Tissue sarcomas (STS) are a group of heterogeneous and complex diseases where being able to predict the appearance of metastases is key to inform clinical decisions, especially the prescription of adjuvant chemotherapy. We developed SarcNet: a m...

Integrating deep learning and radiomics for preoperative glioma grading using multi-center MRI data.

Scientific reports
Accurate preoperative glioma grading remains a critical challenge in neuro-oncology. This study presents a novel integrated approach combining deep learning architectures with radiomics features derived from multi-parametric MRI to improve preoperati...

Exploring the therapeutic effects of continuous kidney replacement therapy in patients with severe acidosis using deep learning-based causal inference.

Scientific reports
Continuous kidney replacement therapy (CKRT) is an essential treatment for uncontrolled severe metabolic acidosis. However, CKRT can increase workload and lead to complications, thus necessitating its selective application to patients who stand to be...