AIMC Topic: Machine Learning

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A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...

Machine Learning-Based Human Recognition Scheme Using a Doppler Radar Sensor for In-Vehicle Applications.

Sensors (Basel, Switzerland)
In this paper, we propose a Doppler spectrum-based passenger detection scheme for a CW (Continuous Wave) radar sensor in vehicle applications. First, we design two new features, referred to as an 'extended degree of scattering points' and a 'differen...

Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study.

Scientific reports
The rapid spread of COVID-19 has resulted in the shortage of medical resources, which necessitates accurate prognosis prediction to triage patients effectively. This study used the nationwide cohort of South Korea to develop a machine learning model ...

Machine learning enables improved runtime and precision for bio-loggers on seabirds.

Communications biology
Unravelling the secrets of wild animals is one of the biggest challenges in ecology, with bio-logging (i.e., the use of animal-borne loggers or bio-loggers) playing a pivotal role in tackling this challenge. Bio-logging allows us to observe many aspe...

Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.

Nature communications
Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational...

Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study.

BMC pediatrics
BACKGROUND: Stunting affects up to one-third of the children in low-to-middle income countries (LMICs) and has been correlated with decline in cognitive capacity and vaccine immunogenicity. Early identification of infants at risk is critical for earl...

Deep Learning Total Energies and Orbital Energies of Large Organic Molecules Using Hybridization of Molecular Fingerprints.

Journal of chemical information and modeling
The ability to predict material properties without the need for resource-consuming experimental efforts can immensely accelerate material and drug discovery. Although ab initio methods can be reliable and accurate in making such predictions, they are...

Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning.

Scientific reports
Eye movements are disrupted in many neurodegenerative diseases and are frequent and early features in conditions affecting the cerebellum. Characterizing eye movements is important for diagnosis and may be useful for tracking disease progression and ...

Comparison of manual and machine learning image processing approaches to determine fungiform papillae on the tongue.

Scientific reports
Human taste perception is associated with the papillae on the tongue as they contain a large proportion of chemoreceptors for basic tastes and other chemosensation. Especially the density of fungiform papillae (FP) is considered as an index for respo...

Combining structured and unstructured data for predictive models: a deep learning approach.

BMC medical informatics and decision making
BACKGROUND: The broad adoption of electronic health records (EHRs) provides great opportunities to conduct health care research and solve various clinical problems in medicine. With recent advances and success, methods based on machine learning and d...