AIMC Topic: Algorithms

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Simulation of time-series groundwater parameters using a hybrid metaheuristic neuro-fuzzy model.

Environmental science and pollution research international
The estimation of qualitative and quantitative groundwater parameters is an essential task. In this regard, artificial intelligence (AI) techniques are extensively utilized as accurate, trustworthy, and cost-effective tools. In the present paper, two...

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

European radiology
BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial in...

Facial expression recognition based on deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Facial expression recognition technology will play an increasingly important role in our daily life. Autonomous driving, virtual reality and all kinds of robots integrated into our life depend on the development of facial ex...

Random vector functional link with ε-insensitive Huber loss function for biomedical data classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Biomedical data classification has been a trending topic among researchers during the last decade. Biomedical datasets may contain several features noises. Hence, the conventional machine learning model cannot efficiently ha...

Artificial intelligence for breast cancer analysis: Trends & directions.

Computers in biology and medicine
Breast cancer is one of the leading causes of death among women. Early detection of breast cancer can significantly improve the lives of millions of women across the globe. Given importance of finding solution/framework for early detection and diagno...

PanClassif: Improving pan cancer classification of single cell RNA-seq gene expression data using machine learning.

Genomics
Cancer is one of the major causes of human death per year. In recent years, cancer identification and classification using machine learning have gained momentum due to the availability of high throughput sequencing data. Using RNA-seq, cancer researc...

Predicting liver cancers using skewed epidemiological data.

Artificial intelligence in medicine
Liver Cancer is a threat to human health and life over the world. The key to reduce liver cancer incidence is to identify high-risk populations and carry out individualized interventions before cancer occurrence. Building predictive models based on m...

Precipitate-Supported Thermal Proteome Profiling Coupled with Deep Learning for Comprehensive Screening of Drug Target Proteins.

ACS chemical biology
Although thermal proteome profiling (TPP) acts as a popular modification-free approach for drug target deconvolution, some key problems are still limiting screening sensitivity. In the prevailing TPP workflow, only the soluble fractions are analyzed ...

Water Quality Indicator Interval Prediction in Wastewater Treatment Process Based on the Improved BES-LSSVM Algorithm.

Sensors (Basel, Switzerland)
This paper proposes a novel interval prediction method for effluent water quality indicators (including biochemical oxygen demand (BOD) and ammonia nitrogen (NH3-N)), which are key performance indices in the water quality monitoring and control of a ...

Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach.

Sensors (Basel, Switzerland)
A pivotal topic in agriculture and food monitoring is the assessment of the quality and ripeness of agricultural products by using non-destructive testing techniques. Acoustic testing offers a rapid in situ analysis of the state of the agricultural g...