Machine Learning - AI Medical Compendium

CO emissions have been steadily increasing and have been a major contributor for climate change compelling nations to take decisive action fast. The average global temperature could reach 1.5 °C by 2035 which could cause a significant impact on the e...

Carbon Carbon Dioxide Climate Change Carbon Sequestration Machine Learning Adsorption

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Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

IEEE transactions on medical imaging Sep 3, 2024

Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced multi-class classification problem in machine learning. It is challenging due to the class imbalance issue and the heterogeneity of the disease. Recentl...

Alzheimer Disease Image Interpretation, Computer-Assisted Male Magnetic Resonance Imaging Aged, 80 and over Algorithms Brain Female Neural Networks, Computer Aged Machine Learning Humans

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Personalized Federated Graph Learning on Non-IID Electronic Health Records.

IEEE transactions on neural networks and learning systems Sep 3, 2024

Understanding the latent disease patterns embedded in electronic health records (EHRs) is crucial for making precise and proactive healthcare decisions. Federated graph learning-based methods are commonly employed to extract complex disease patterns ...

Algorithms Electronic Health Records Machine Learning Humans Neural Networks, Computer

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Higher Order Polynomial Transformer for Fine-Grained Freezing of Gait Detection.

IEEE transactions on neural networks and learning systems Sep 3, 2024

Freezing of Gait (FoG) is a common symptom of Parkinson's disease (PD), manifesting as a brief, episodic absence, or marked reduction in walking, despite a patient's intention to move. Clinical assessment of FoG events from manual observations by exp...

Machine Learning Algorithms Humans Neural Networks, Computer Gait Disorders, Neurologic Parkinson Disease Gait Deep Learning

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Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.

IEEE transactions on neural networks and learning systems Sep 3, 2024

With the adoption of smart systems, artificial neural networks (ANNs) have become ubiquitous. Conventional ANN implementations have high energy consumption, limiting their use in embedded and mobile applications. Spiking neural networks (SNNs) mimic ...

Animals Deep Learning Algorithms Action Potentials Neurons Image Processing, Computer-Assisted Models, Neurological Humans Neural Networks, Computer Machine Learning

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AIMC Topic: Machine Learning

Patient Diversity and Collaborative Co-Reasoning for Ethical Use of Machine Learning-Driven Decision Support Systems.

A Knower Without a Voice: Co-Reasoning with Machine Learning.

A Holistic, Multi-Level, and Integrative Ethical Approach to Developing Machine Learning-Driven Decision Aids.

Transparency, Evaluation and Going From "Ethics-Washing" to Enforceable Regulation: On Machine Learning-Driven Clinician Decision Aids.

Co-reasoning by Humans in the Loop as a Goal for Designers of Machine Learning-Driven Algorithms in Medicine.

Leveraging experimental and computational tools for advancing carbon capture adsorbents research.

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

Personalized Federated Graph Learning on Non-IID Electronic Health Records.

Higher Order Polynomial Transformer for Fine-Grained Freezing of Gait Detection.

Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.

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AIMC Topic: Machine Learning

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