Beyond 3-D: Data scientists introduce novel AI tool to interpret complex biological data

As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess ...
JD Supra

Feeding the Machine: Improving Population Health Analyses Through AI Tools

With the increased need for data to support artificial intelligence (AI) and large language models, data aggregation and de-identification are ...

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 ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

When to Use Standardization and Normalization: Empirical Evidence From Machine Learning Models and XAI

Abstract: Optimizing machine learning (ML) model performance relies heavily on appropriate data preprocessing techniques. Despite the widespread use of standardization and normalization, empirical ...
GitHub

libpostal: international street address NLP

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ahajournals.org

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time–International Normalized Ratio and Activated Partial ...

Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable medication history. We investigated whether routinely available ...