Author Archives:
UWMadison part of effort to advance fusion energy with machine … – University of Wisconsin-Madison
Steffi Diem (middle) participating in a panel at the White House Summit on Developing a Bold Decadal Vision for Commercial Fusion Energy. Diem has joined a collaboration across multiple institutions that will use machine learning to better understand magnetic fusion energy. Researchers at the University of WisconsinMadison are taking part in a new collaboration built on open-science principles that will use machine learning to advance our knowledge of promising sources of magnetic fusion energy
Machine learning tool simplifies one of the most widely used reactions in the pharmaceutical industry – Phys.org
This article has been reviewed according to ScienceX's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: fact-checked peer-reviewed publication trusted source proofread close In the past two decades, the carbon-nitrogen bond forming reaction, known as the Buchwald-Hartwig reaction, has become one of the most widely used tools in organic synthesis, particularly in the pharmaceutical industry given the prevalence of nitrogen in natural products and pharmaceuticals
Revolutionizing Drug Development Through Artificial Intelligence … – Pharmacy Times
The field of drug development stands at a pivotal crossroads, where the convergence of technological advancements and medical innovation is transforming traditional paradigms. At the forefront of this transformation lies artificial intelligence (AI) and machine learning (ML), powerful tools that are revolutionizing the drug discovery and development processes
Open source in machine learning: experts weigh in on the future – CryptoTvplus
In a recent event by the University of California, Berkeley, focused on Open Source vs. Closed Source: Will Open Source Win?
Machine-Learning Tool Sorts Tics From Non-Tics on Video – Medscape
COPENHAGEN A novel machine-learning tool that can distinguish between tics in patients with tic disorders and non-tic movements in healthy controls could potentially save clinicians time and improve the accuracy of tic identification, German researchers suggest. Videos of more than 60 people with tic disorders were assessed manually to provide a set of clinical features related to facial tics
Machine learning and thought, climate impact on health, Alzheimer’s … – Virginia Tech
One of the worlds leaders in computational psychiatry will kick off the upcomingMaury Strauss Distinguished Public Lecture Seriesat the Fralin Biomedical Research Institute at VTC in September.
Machine Learning Regularization Explained With Examples – TechTarget
What is regularization in machine learning?
Advanced Space-led Team Applying Machine Learning to Detect … – Space Ref
Advanced Space LLC., a leading space tech solutions company, is pleased to announce that an Advanced Space-led team has been chosen to apply Machine Learning (ML) capabilities to detect, track and characterize space debris for the IARPA Space Debris Identification and Tracking (SINTRA) program. Space debrisitems due to human activity in spacepresents a major hazard to space operations. Advanced Space and its teammates Orion Space Solutions and ExoAnalytic Solutions are applying advanced ML techniques to finding and identifying small debris (0.1-10 cm) under a new Space Debris Identification and Tracking (SINTRA) contract from Intelligence Advanced Research Projects Activity (IARPA)
Machine Learning, Numerical Simulation Integrated To Estimate … – Society of Petroleum Engineers
In the complete paper, the authors analyzed a robust, well-distributed parent/child well data set of the Delaware Basin Wolfcamp formation using a combination of available empirical data and numerical simulation outputs, which was used to develop a predictive machine-learning model (consisting of a multiple linear regression model and a simple neural network). This model has been implemented successfully in field developments to optimize child-well placement and has enabled improvements in performance predictions and net present value.