AIMC Topic: Neural Networks, Computer

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EffiViT: Hybrid CNN-Transformer for Retinal Imaging.

Computers in biology and medicine
The human eye is a vital sensory organ that is crucial for visual perception. The retina is the main component of the eye and is responsible for visual signals. Due to its characteristics, the retina can reveal the occurrence of ocular diseases. So, ...

Attention in surgical phase recognition for endoscopic pituitary surgery: Insights from real-world data.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Surgical Phase Recognition systems are used to support the automated documentation of a procedure and to provide the surgical team with real-time feedback, potentially improving surgical outcome and reducing adverse events. ...

A new lightweight deep learning model optimized with pruning and dynamic quantization to detect freezing gait on wearable devices.

Computers in biology and medicine
Freezing of gait (FoG) is a debilitating symptom of Parkinson's disease that severely impacts patients' mobility and quality of life. To minimize the risk of falls and injuries associated with FoG, it is crucial to develop highly accurate FoG detecti...

A deep learning framework leveraging spatiotemporal feature fusion for electrophysiological source imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Electrophysiological source imaging (ESI) is a challenging technique for noninvasively measuring brain activity, which involves solving a highly ill-posed inverse problem. Traditional methods attempt to address this challen...

Portable ECG and PCG wireless acquisition system and multiscale CNN feature fusion Bi-LSTM network for coronary artery disease diagnosis.

Computers in biology and medicine
Coronary artery disease (CAD) is a major cause of mortality, especially among aging populations, making timely and accurate diagnosis essential. In this work, a portable wireless device powered by artificial intelligence for CAD detection is proposed...

Atten-Nonlocal Unet: Attention and Non-local Unet for medical image segmentation.

Computers in biology and medicine
The convolutional neural network(CNN)-based models have emerged as the predominant approach for medical image segmentation due to their effective inductive bias. However, their limitation lies in the lack of long-range information. In this study, we ...

Beyond binding: from modular to natural vision.

Trends in cognitive sciences
The classical view of visual cortex organization as a collection of specialized modules processing distinct features like color and motion has profoundly influenced neuroscience for decades. This framework, rooted in historical philosophical distinct...

A multi-scale convolutional LSTM-dense network for robust cardiac arrhythmia classification from ECG signals.

Computers in biology and medicine
Cardiac arrhythmias are irregular heart rhythms that, if undetected, can lead to severe cardiovascular conditions. Detecting these anomalies early through electrocardiogram (ECG) signal analysis is critical for preventive healthcare and effective tre...

Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Computers in biology and medicine
Parkinson's disease (PD) is characterised by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disruptions in neuroactive metabolites. Dysregulated activity of tryptophan 2,3-dioxygenase (TDO), a key en...

Lag-Net: Lag correction for cone-beam CT via a convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Due to the presence of charge traps in amorphous silicon flat-panel detectors, lag signals are generated in consecutively captured projections. These signals lead to ghosting in projection images and severe lag artifacts in ...