In this study, the impact of thermal effects on the orbit of an asteroid is investigated. This included determining if the asteroid's orbit would push into a region devoid of asteroids due to the gravitational pull of Jupiter.
Read More...Predicting Orbital Resonance of 2867 Šteins Using the Yarkovsky Effect
In this study, the impact of thermal effects on the orbit of an asteroid is investigated. This included determining if the asteroid's orbit would push into a region devoid of asteroids due to the gravitational pull of Jupiter.
Read More...Part of speech distributions for Grimm versus artificially generated fairy tales
Here, the authors wanted to explore mathematical paradoxes in which there are multiple contradictory interpretations or analyses for a problem. They used ChatGPT to generate a novel dataset of fairy tales. They found statistical differences between the artificially generated text and human produced text based on the distribution of parts of speech elements.
Read More...Advancing pediatric cancer predictions through generative artificial intelligence and machine learning
Pediatric cancers pose unique challenges due to their rarity and distinct biological factors, emphasizing the need for accurate survival prediction to guide treatment. This study integrated generative AI and machine learning, including synthetic data, to analyze 9,184 pediatric cancer patients, identifying age at diagnosis, cancer types, and anatomical sites as significant survival predictors. The findings highlight the potential of AI-driven approaches to improve survival prediction and inform personalized treatment strategies, with broader implications for innovative healthcare applications.
Read More...COVID-19 and air pollution in New York City
Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.
Read More...Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease
Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).
Read More...Using two-step machine learning to predict harmful algal bloom risk
Using machine learning to predict the risk of algae bloom
Read More...A comparative analysis of machine learning approaches to predict brain tumors using MRI
The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.
Read More...Deuterated solvent effects in the kinetics and thermodynamics of keto-enol tautomerization of ETFAA
In this study, the authors determined whether tautomerization dynamics in protic and aprotic solvents displayed differences in reaction rates and in the proportion of the keto and enol tautomers present.
Read More...India’s digital public infrastructure: Analyzing UPI and Aadhaar in GDP growth and cost optimization
India’s Digital Public Infrastructure (DPI)—including the Unified Payments Interface (UPI) and Aadhaar—has been globally recognized for advancing financial inclusion and efficient governance. This study analyzes data from 2016–17 to 2023–24 the impact of these services on India's GDP.
Read More...Deep dive into predicting insurance premiums using machine learning
The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.
Read More...