AIMC Topic: Algorithms

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AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.

IEEE transactions on medical imaging
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible. While AI models f...

Deep Generalized Learning Model for PET Image Reconstruction.

IEEE transactions on medical imaging
Low-count positron emission tomography (PET) imaging is challenging because of the ill-posedness of this inverse problem. Previous studies have demonstrated that deep learning (DL) holds promise for achieving improved low-count PET image quality. How...

Classification of attention deficit hyperactivity disorder using machine learning on an EEG dataset.

Applied neuropsychology. Child
The neurodevelopmental disorder, Attention Deficit Hyperactivity Disorder (ADHD), frequently affecting youngsters, is characterized by persistent patterns of inattention, hyperactivity, and impulsivity, the etiology of which may involve a variety of ...

Deep learning applications in protein crystallography.

Acta crystallographica. Section A, Foundations and advances
Deep learning techniques can recognize complex patterns in noisy, multidimensional data. In recent years, researchers have started to explore the potential of deep learning in the field of structural biology, including protein crystallography. This f...

Deep residual networks for crystallography trained on synthetic data.

Acta crystallographica. Section D, Structural biology
The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and tra...

DeepQs: Local quality assessment of cryo-EM density map by deep learning map-model fit score.

Journal of structural biology
Cryogenic electron microscopy maps are valuable for determining macromolecule structures. A proper quality assessment method is essential for cryo-EM map selection or revision. This article presents DeepQs, a novel approach to estimate local quality ...

Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning.

Computers in biology and medicine
Pathology diagnosis based on EEG signals and decoding brain activity holds immense importance in understanding neurological disorders. With the advancement of artificial intelligence methods and machine learning techniques, the potential for accurate...

Effluent parameters prediction of a biological nutrient removal (BNR) process using different machine learning methods: A case study.

Journal of environmental management
This paper proposes a novel targeted blend of machine learning (ML) based approaches for controlling wastewater treatment plant (WWTP) operation by predicting distributions of key effluent parameters of a biological nutrient removal (BNR) process. Tw...

Reclassification of ASFV into 7 Biotypes Using Unsupervised Machine Learning.

Viruses
In 2007, an outbreak of African swine fever (ASF), a deadly disease of domestic swine and wild boar caused by the African swine fever virus (ASFV), occurred in Georgia and has since spread globally. Historically, ASFV was classified into 25 different...

Advancements in artificial intelligence algorithms for dental implant identification: A systematic review with meta-analysis.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: The evidence regarding the application of artificial intelligence (AI) in identifying dental implant systems is currently inconclusive. The available studies present varying results and methodologies, making it difficult to draw...