AIMC Topic: Algorithms

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Boosting wisdom of the crowd for medical image annotation using training performance and task features.

Cognitive research: principles and implications
A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recr...

Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin.

PeerJ
BACKGROUND: The Yunnan section of the Nujiang River (YNR) Basin in the alpine-valley area is one of the most critical areas of debris flow in China.

A novel fusion of genetic grey wolf optimization and kernel extreme learning machines for precise diabetic eye disease classification.

PloS one
In response to the growing number of diabetes cases worldwide, Our study addresses the escalating issue of diabetic eye disease (DED), a significant contributor to vision loss globally, through a pioneering approach. We propose a novel integration of...

An integrated group decision-making method under q-rung orthopair fuzzy 2-tuple linguistic context with partial weight information.

PloS one
Considering the advantages of q-rung orthopair fuzzy 2-tuple linguistic set (q-RFLS), which includes both linguistic and numeric data to describe evaluations, this article aims to design a new decision-making methodology by integrating Vlsekriterijum...

FPNC Net: A hydrogenation catalyst image recognition algorithm based on deep learning.

PloS one
The identification research of hydrogenation catalyst information has always been one of the most important businesses in the chemical industry. In order to aid researchers in efficiently screening high-performance catalyst carriers and tackle the pr...

TASA: Temporal Attention With Spatial Autoencoder Network for Odor-Induced Emotion Classification Using EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The olfactory system enables humans to smell different odors, which are closely related to emotions. The high temporal resolution and non-invasiveness of Electroencephalogram (EEG) make it suitable to objectively study human preferences for odors. Ef...

s-TBN: A New Neural Decoding Model to Identify Stimulus Categories From Brain Activity Patterns.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neural decoding is still a challenging and a hot topic in neurocomputing science. Recently, many studies have shown that brain network patterns containing rich spatiotemporal structural information represent the brain's activation information under e...

Geographical origin identification of Khao Dawk Mali 105 rice using combination of FT-NIR spectroscopy and machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The mislabelled Khao Dawk Mali 105 rice coming from other geographical region outside the Thung Kula Rong Hai region is extremely profitable and difficult to detect; to prevent retail fraud (that adversely affects both the food industry and consumers...

Unlocking the full potential of mesenchymal stromal cell therapy for osteoarthritis through machine learning-based in silico trials.

Cytotherapy
Despite the potential of mesenchymal stromal cells (MSCs) in osteoarthritis (OA) treatment, the challenge lies in addressing their therapeutic inconsistency. Clinical trials revealed significantly varied therapeutic outcomes among patients receiving ...

Evaluating tooth segmentation accuracy and time efficiency in CBCT images using artificial intelligence: A systematic review and Meta-analysis.

Journal of dentistry
OBJECTIVES: This systematic review and meta-analysis aimed to assess the current performance of artificial intelligence (AI)-based methods for tooth segmentation in three-dimensional cone-beam computed tomography (CBCT) images, with a focus on their ...