Machine Learning Is Enabling A New Era For Precision Medicine And Pharmacogenomics

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Machine learning rediscovers equations governing ocean biogeochemistry

Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...

AI teaches asset traders not to sweat the small stuff

Financial markets are governed by a combination of rational and irrational forces, statistical probabilities and "animal ...
AlphaGalileo

Transfer learning boosts leaf trait estimation from space

Leaf functional traits—chlorophyll (CHL), carotenoid (CAR), equivalent water thickness (EWT), nitrogen (N), and leaf mass per ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...
Frontiers

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
Frontiers

Enhancing disaster prediction with Bayesian deep learning: a robust approach for uncertainty estimation

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...
LinkedIn

The Great Divide: Bayesian Algorithms vs. Hebbian Learning in the Quest for Intelligent Machines

In the vast landscape of machine learning, few comparisons are as intellectually stimulating as that between Bayesian algorithms and Hebbian learning. These two paradigms represent fundamentally ...
Nature

Developing machine learning for heterogeneous catalysis with experimental and computational data

ANN (artificial neural network): a computational model inspired by the structure and function of biological neural networks, capable of learning complex nonlinear relationships in data BLR (Bayesian ...
Medical Xpress

Bayesian learning boosts gene research accuracy

Researchers at The University of Texas at Arlington have developed a new computational tool that helps scientists pinpoint proteins known as transcriptional regulators that control how genes turn on ...
C&EN

Bayesian Optimization with Gaussian Processes Assisted by Deep Learning for Material Designs

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Developing novel materials drives significant breakthroughs ...