AIMC Topic: Machine Learning

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A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.

PloS one Nov 9, 2021
INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) ...
Hernias, Diaphragmatic, Congenital Lung Pregnancy Deep Learning Female Magnetic Resonance Imaging Extracorporeal Membrane Oxygenation Infant, Newborn Hypertension, Pulmonary Humans Prenatal Diagnosis Machine Learning Retrospective Studies
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Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models.

Environmental science and pollution research international Nov 8, 2021
Forecasting the irrigation groundwater parameters helps plan irrigation water and crop, and it is commonly expensive because it needs various parameters, mainly in developing nations. Therefore, the present research's core objective is to create accu...
Neural Networks, Computer Machine Learning Groundwater Water Quality Linear Models
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Performance comparison of deep learning and machine learning methods in determining wetland water areas using EuroSAT dataset.

Environmental science and pollution research international Nov 8, 2021
Wetlands are critical to the ecology because they maintain biodiversity and provide home for a variety of species. Researching, mapping, and conservation of wetlands is a challenging and time-consuming process. Because they produce temporal and geogr...
Water Support Vector Machine Wetlands Neural Networks, Computer Machine Learning Deep Learning
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Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning.

Histochemistry and cell biology Nov 8, 2021
Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tis...
Machine Learning Animals Image Processing, Computer-Assisted Spectroscopy, Fourier Transform Infrared Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Oligochaeta Digestive System
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A transfer learning approach for predictive modeling of bioprocesses using small data.

Biotechnology and bioengineering Nov 8, 2021
Predictive modeling of new biochemical systems with small data is a great challenge. To fill this gap, transfer learning, a subdomain of machine learning that serves to transfer knowledge from a generalized model to a more domain-specific model, prov...
Models, Biological Microalgae Machine Learning Lutein Biomass Kinetics Chlorophyceae
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Phybrata Sensors and Machine Learning for Enhanced Neurophysiological Diagnosis and Treatment.

Sensors (Basel, Switzerland) Nov 8, 2021
Concussion injuries remain a significant public health challenge. A significant unmet clinical need remains for tools that allow related physiological impairments and longer-term health risks to be identified earlier, better quantified, and more easi...
Machine Learning Algorithms Support Vector Machine Monitoring, Physiologic Humans Neural Networks, Computer
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Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis.

Journal of Korean medical science Nov 8, 2021
BACKGROUND: This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (GERD) and periodontitis.
Gastroesophageal Reflux Social Class Adult Logistic Models Periodontitis Pregnancy Databases, Factual Female Retrospective Studies Premature Birth Republic of Korea Humans Machine Learning
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Estimating severe fever with thrombocytopenia syndrome transmission using machine learning methods in South Korea.

Scientific reports Nov 8, 2021
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease in China, Japan, and Korea. This study aimed to estimate the monthly SFTS occurrence and the monthly number of SFTS cases in the geographical area in Kore...
Epidemiological Models Mountaineering Severe Fever with Thrombocytopenia Syndrome Climate Travel-Related Illness Middle Aged Humans Regression Analysis Machine Learning Aged Republic of Korea Computer Simulation Male Female Risk Factors
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Machine learning random forest for predicting oncosomatic variant NGS analysis.

Scientific reports Nov 8, 2021
Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but ...
Databases, Genetic Models, Statistical Genetic Variation ROC Curve Polymorphism, Single Nucleotide Computational Biology High-Throughput Nucleotide Sequencing INDEL Mutation Oncogenes Neural Networks, Computer Machine Learning Algorithms Biomarkers, Tumor Neoplasms Deep Learning Humans
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An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila.

Genome biology Nov 8, 2021
BACKGROUND: Enhancers are non-coding regions of the genome that control the activity of target genes. Recent efforts to identify active enhancers experimentally and in silico have proven effective. While these tools can predict the locations of enhan...
Artificial Intelligence Machine Learning Animals Epigenesis, Genetic Histone Code High-Throughput Nucleotide Sequencing Drosophila melanogaster Drosophila Proteins Molecular Sequence Annotation Promoter Regions, Genetic Enhancer Elements, Genetic
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