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Found 9 papers, 3 papers with code
Machine Learning-Based Analysis of Ebola Virus' Impact on Gene Expression in Nonhuman Primates
This study introduces the Supervised Magnitude-Altitude Scoring (SMAS) methodology, a machine learning-based approach, for analyzing gene expression data obtained from nonhuman primates (NHPs) infected with Ebola virus (EBOV).
Machine Learning Based Analytics for the Significance of Gait Analysis in Monitoring and Managing Lower Extremity Injuries
XGBoost was the optimal model both before and after applying SMOTE.
Cross-attention-based saliency inference for predicting cancer metastasis on whole slide images
Apart from this new attention mechanism, we introduce a negative representation learning algorithm to facilitate the learning of saliency-informed attention weights for improved sensitivity on tumor WSIs.
Attention2Minority: A salient instance inference-based multiple instance learning for classifying small lesions in whole slide images
Our method initially learns representations of normal WSIs, and it then compares the normal WSIs representations with all the input patches to infer the salient instances of the input WSI.
Artificial Intelligence-Based Analytics for Impacts of COVID-19 and Online Learning on College Students' Mental Health
In this paper, we seek to understand how the COVID-19 pandemic and increase in online learning impact college students' emotional wellbeing.
A machine learning analysis of the relationship between some underlying medical conditions and COVID-19 susceptibility
Furthermore, this paper reflects upon conclusions made about the relationship between educational attainment, race, and COVID-19 and the possible connections that can be established with underlying health conditions, vaccination rates, and COVID-19 total case and death counts.
A Machine Learning Analysis of Impact of the Covid-19 Pandemic on Alcohol Consumption Habit Changes Among Healthcare Workers in the U.S
In this paper, we discuss the impact of the Covid-19 pandemic on alcohol consumption habit changes among healthcare workers in the United States.
A Machine Learning Analysis of COVID-19 Mental Health Data
Through the interpretation of the many models applied to the mental health survey data, we have concluded that the most important factor in predicting the mental health decline of a frontline worker is the healthcare role the individual is in (Nurse, Emergency Room Staff, Surgeon, etc.
Neural-trust-region algorithm for unconstrained optimization (Part 1)
In this paper (part 1), we describe a derivative-free trust-region method for solving unconstrained optimization problems.
Optimization and Control
