AIMC Topic: Machine Learning

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Spectroscopy-based chemometrics combined machine learning modeling predicts cashew foliar macro- and micronutrients.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Precision nutrient management in orchard crops needs precise, accurate, and real-time information on the plant's nutritional status. This is limited by the fact that it requires extensive leaf sampling and chemical analysis when it is to be done over...

Exploring liquid-liquid phase separation-related diagnostic biomarkers in osteoarthritis based on machine learning algorithms and experiment.

Immunobiology
BACKGROUND: Osteoarthritis (OA) is a prevalent joint disorder characterized by cartilage degeneration and joint inflammation. Liquid-liquid phase separation (LLPS), a biophysical process involved in cellular organization, has recently gained attentio...

Machine learning and CORDEX-Africa regional model for assessing the impact of climate change on the Gilgel Gibe Watershed, Ethiopia.

Journal of environmental management
Climate change is one of the most pressing challenges of our time, profoundly impacting global water resources and sustainability. This study aimed to predict the long-term effects of climate change on the Gilgel Gibe watershed by integrating machine...

Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence.

Sensors (Basel, Switzerland)
Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enab...

Identification of Respiratory Pauses during Swallowing by Unconstrained Measuring Using Millimeter Wave Radar.

Sensors (Basel, Switzerland)
Breathing temporarily pauses during swallowing, and the occurrence of inspiration before and after these pauses may increase the likelihood of aspiration, a serious health problem in older adults. Therefore, the automatic detection of these pauses wi...

Motor assessment of X-linked dystonia parkinsonism via machine-learning-based analysis of wearable sensor data.

Scientific reports
X-linked dystonia parkinsonism (XDP) is a neurogenetic combined movement disorder involving both parkinsonism and dystonia. Complex, overlapping phenotypes result in difficulties in clinical rating scale assessment. We performed wearable sensor-based...

The relationship between design-based lateralization, humeral bearing design, polyethylene angle, and patient-related factors on surgical complications after reverse shoulder arthroplasty: a machine learning analysis.

Journal of shoulder and elbow surgery
BACKGROUND: Technological advancements in implant design and surgical technique have focused on diminishing complications and optimizing performance of reverse shoulder arthroplasty (rTSA). Despite this, there remains a paucity of literature correlat...

Precision classification and quantitative analysis of bacteria biomarkers via surface-enhanced Raman spectroscopy and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The SERS spectra of six bacterial biomarkers, 2,3-DHBA, 2,5-DHBA, Pyocyanin, lipoteichoic acid (LTA), Enterobactin, and β-carotene, of various concentrations, were obtained from silver nanorod array substrates, and the spectral peaks and the correspo...

Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...

Using machine learning to unveil relevant predictors of adherence to recommended health-protective behaviors during the COVID-19 pandemic in Denmark.

Applied psychology. Health and well-being
What were relevant predictors of individuals' proclivity to adhere to recommended health-protective behaviors during the COVID-19 pandemic in Denmark? Applying machine learning (namely, lasso regression) to a repeated cross-sectional survey spanning ...