AIMC Topic: Neural Networks, Computer

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RECOMED: A comprehensive pharmaceutical recommendation system.

Artificial intelligence in medicine
OBJECTIVES: To build datasets containing useful information from drug databases and recommend a list of drugs to physicians and patients with high accuracy by considering a wide range of features of people, diseases, and chemicals.

Recurrent neural network-aided processing of incomplete free induction decays in H-MRS of the brain.

Journal of magnetic resonance (San Diego, Calif. : 1997)
In the case of limited sampling windows or truncation of free induction decays (FIDs) for artifact removal in proton magnetic resonance spectroscopy (H-MRS) and spectroscopic imaging (H-MRSI), metabolite quantification needs to be performed on incomp...

Encoding innate ability through a genomic bottleneck.

Proceedings of the National Academy of Sciences of the United States of America
Animals are born with extensive innate behavioral capabilities, which arise from neural circuits encoded in the genome. However, the information capacity of the genome is orders of magnitude smaller than that needed to specify the connectivity of an ...

Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals.

Sensors (Basel, Switzerland)
This research examines the application of non-invasive acoustic analysis for detecting obstructions in vascular access (fistulas) used by kidney dialysis patients. Obstructions in these fistulas can interrupt essential dialysis treatment. In this stu...

Mild cognitive impairment prediction based on multi-stream convolutional neural networks.

BMC bioinformatics
BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Cur...

Training and validation of a deep learning U-net architecture general model for automated segmentation of inner ear from CT.

European radiology experimental
BACKGROUND: The intricate three-dimensional anatomy of the inner ear presents significant challenges in diagnostic procedures and critical surgical interventions. Recent advancements in deep learning (DL), particularly convolutional neural networks (...

Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review.

Journal of medical systems
In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the selection of appropriate computational models is critical for accurate diagnosis and patient care. This literature review provides a comprehensive com...

STransU2Net: Transformer based hybrid model for building segmentation in detailed satellite imagery.

PloS one
As essential components of human society, buildings serve a multitude of functions and significance. Convolutional Neural Network (CNN) has made remarkable progress in the task of building extraction from detailed satellite imagery, owing to the pote...

Enhancing reginal wall abnormality detection accuracy: Integrating machine learning, optical flow algorithms, and temporal convolutional networks in multi-view echocardiography.

PloS one
BACKGROUND: Regional Wall Motion Abnormality (RWMA) serves as an early indicator of myocardial infarction (MI), the global leader in mortality. Accurate and early detection of RWMA is vital for the successful treatment of MI. Current automated echoca...