AIMC Topic: Machine Learning

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High alert drugs screening using gradient boosting classifier.

Scientific reports
Prescription errors in high alert drugs (HAD), a group of drugs that have a high risk of complications and potential negative consequences, are a major and serious problem in medicine. Standardized hospital interventions, protocols, or guidelines wer...

Genetic variant effect prediction by supervised nonnegative matrix tri-factorization.

Molecular omics
Discriminating between deleterious and neutral mutations among numerous non-synonymous single nucleotide variants (nsSNVs) that may be observed through whole exome sequencing (WES) is considered a great challenge. In this regard, many machine learnin...

Artificial intelligence forecasting mortality at an intensive care unit and comparison to a logistic regression system.

Einstein (Sao Paulo, Brazil)
OBJECTIVE: To explore an artificial intelligence approach based on gradient-boosted decision trees for prediction of all-cause mortality at an intensive care unit, comparing its performance to a recent logistic regression system in the literature, an...

Detecting phishing websites using machine learning technique.

PloS one
In recent years, advancements in Internet and cloud technologies have led to a significant increase in electronic trading in which consumers make online purchases and transactions. This growth leads to unauthorized access to users' sensitive informat...

Comparative optimization of global solar radiation forecasting using machine learning and time series models.

Environmental science and pollution research international
The increasing use of solar energy as a source of renewable energy has led to increasing the interest in photovoltaic (PV) power outputs forecasting. In the meantime, forecasting global solar radiation (GSR) depends heavily on weather conditions, whi...

Stem-cell based, machine learning approach for optimizing natural killer cell-based personalized immunotherapy for high-grade ovarian cancer.

The FEBS journal
Advanced high-grade serous ovarian cancer continues to be a therapeutic challenge for those affected using the current therapeutic interventions. There is an increasing interest in personalized cancer immunotherapy using activated natural killer (NK)...

Prediction for understanding the effectiveness of antiviral peptides.

Computational biology and chemistry
The low efficacy of current antivirals in conjunction with the resistance of viruses against existing antiviral drugs has resulted in the demand for the development of novel antiviral agents. Antiviral peptides (AVPs) are those bioactive peptides hav...

Coupling of Trastuzumab chromatographic profiling with machine learning tools: A complementary approach for biosimilarity and stability assessment.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Biosimilar products present a growing opportunity to improve the global healthcare systems. The amount of accepted variability during the comparative assessments of biosimilar products introduces a significant challenge for both the biosimilar develo...

A practical approach towards causality mining in clinical text using active transfer learning.

Journal of biomedical informatics
OBJECTIVE: Causality mining is an active research area, which requires the application of state-of-the-art natural language processing techniques. In the healthcare domain, medical experts create clinical text to overcome the limitation of well-defin...

Mortality-Risk Prediction Model from Road-Traffic Injury in Drunk Drivers: Machine Learning Approach.

International journal of environmental research and public health
BACKGROUND: Alcohol-related road-traffic injury is the leading cause of premature death in middle- and lower-income countries, including Thailand. Applying machine-learning algorithms can improve the effectiveness of driver-impairment screening strat...