AIMC Topic: Humans

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Taming Prolonged Ionic Drift-Diffusion Dynamics for Brain-Inspired Computation.

Advanced materials (Deerfield Beach, Fla.)
Recent advances in neural network-based computing have enabled human-like information processing in areas such as image classification and voice recognition. However, many neural networks run on conventional computers that operate at GHz clock freque...

Fusing CNNs and attention-mechanisms to improve real-time indoor Human Activity Recognition for classifying home-based physical rehabilitation exercises.

Computers in biology and medicine
Physical rehabilitation plays a critical role in enhancing health outcomes globally. However, the shortage of physiotherapists, particularly in developing countries where the ratio is approximately ten physiotherapists per million people, poses a sig...

Machine-Learning Mental-Fatigue-Measuring μm-Thick Elastic Epidermal Electronics (MMMEEE).

Nano letters
Electrophysiological (EP) signals are key biomarkers for monitoring mental fatigue (MF) and general health, but state-of-the-art wearable EP-based MF monitoring systems are bulky and require user-specific, labeled data. Ultrathin epidermal electrodes...

Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation.

Journal of chemical information and modeling
Cyanobacteria strains have the potential to produce bioactive compounds that can be used in therapeutics and bioremediation. Therefore, compiling all information about these compounds to consider their value as bioresources for industrial and researc...

Metastatic Versus Localized Disease as Inclusion Criteria That Can Be Automatically Extracted From Randomized Controlled Trials Using Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Extracting inclusion and exclusion criteria in a structured, automated fashion remains a challenge to developing better search functionalities or automating systematic reviews of randomized controlled trials in oncology. The question "Did th...

Identification of CCR7 and CBX6 as key biomarkers in abdominal aortic aneurysm: Insights from multi-omics data and machine learning analysis.

IET systems biology
Abdominal aortic aneurysm (AAA) is a severe vascular condition, marked by the progressive dilation of the abdominal aorta, leading to rupture if untreated. The objective of this study was to identify key biomarkers and decipher the immune mechanisms ...

FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification.

IEEE transactions on cybernetics
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning (DL)-based models have achieved superior performance but centralized training suffers from the privacy leakage problem. Federated learning (FL) ca...

Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI.

Sensors (Basel, Switzerland)
Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnost...

Ultrasound Versus Elastography in the Diagnosis of Hepatic Steatosis: Evaluation of Traditional Machine Learning Versus Deep Learning.

Sensors (Basel, Switzerland)
The prevalence of fatty liver disease is on the rise, posing a significant global health concern. If left untreated, it can progress into more serious liver diseases. Therefore, accurately diagnosing the condition at an early stage is essential for m...

Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset.

Sensors (Basel, Switzerland)
The increasing number of individuals with disabilities-over 61 million adults in the United States alone-underscores the urgent need for technologies that enhance autonomy and independence. Among these individuals, millions rely on wheelchairs and of...