AIMC Topic: Algorithms

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Dynamic glucose enhanced imaging using direct water saturation.

Magnetic resonance in medicine
PURPOSE: Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based li...

ECP-GAN: Generating Endometrial Cancer Pathology Images and Segmentation Labels via Two-Stage Generative Adversarial Networks.

Annals of surgical oncology
BACKGROUND: Endometrial cancer is one of the most common tumors of the female reproductive system and ranks third in the world list of gynecological malignancies that cause death. However, due to the privacy and complexity of pathology images, it is ...

LW-CTrans: A lightweight hybrid network of CNN and Transformer for 3D medical image segmentation.

Medical image analysis
Recent models based on convolutional neural network (CNN) and Transformer have achieved the promising performance for 3D medical image segmentation. However, these methods cannot segment small targets well even when equipping large parameters. Theref...

Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning.

Computers in biology and medicine
Digital twins (DTs) are advancing biotechnology by providing digital models for drug discovery, digital health applications, and biological assets, including microorganisms. However, the hypothesis posits that implementing micro- and nanoscale DTs, e...

Machine learning algorithms for predicting membrane bioreactors performance: A review.

Journal of environmental management
Membrane bioreactors (MBR) are recognized as a sustainable technology for treating polluted effluents. Machine learning (ML) algorithms have emerged as a modeling option to predict pollutant removal and operational variables such as membrane fouling,...

Artificial Intelligence: A New Tool for Structure-Based G Protein-Coupled Receptor Drug Discovery.

Biomolecules
Understanding protein structures can facilitate the development of therapeutic drugs. Traditionally, protein structures have been determined through experimental approaches such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy...

A Two stage deep learning network for automated femoral segmentation in bilateral lower limb CT scans.

Scientific reports
This study presents the development of a deep learning-based two-stage network designed for the efficient and precise segmentation of the femur in full lower limb CT images. The proposed network incorporates a dual-phase approach: rapid delineation o...

Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations.

Scientific reports
This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk factors via machine learning techniques. Data from 14,145 workers (627 with occupational noise-induce...

The analysis of Chinese National ballad composition education based on artificial intelligence and deep learning.

Scientific reports
This study focuses on generating national ballads with ethnic characteristics through algorithms, and exploring the application of artificial intelligence in music composition. As an important component of Chinese traditional culture, national ballad...

Boundary-enhanced local-global collaborative network for medical image segmentation.

Scientific reports
Medical imaging plays a vital role as an auxiliary tool in clinical diagnosis and treatment, with segmentation serving as a crucial foundational process in medical image analysis. Nonetheless, challenges such as class imbalance and indistinct boundar...