AIMC Topic: Machine Learning

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Technology Platforms and Approaches for Building and Evaluating Machine Learning Methods in Healthcare.

The journal of applied laboratory medicine
BACKGROUND: Artificial intelligence (AI) methods are becoming increasingly commonly implemented in healthcare as decision support, business intelligence tools, or, in some cases, Food and Drug Administration-approved clinical decision-makers. Advance...

Optimizing Equity: Working towards Fair Machine Learning Algorithms in Laboratory Medicine.

The journal of applied laboratory medicine
BACKGROUND: Methods of machine learning provide opportunities to use real-world data to solve complex problems. Applications of these methods in laboratory medicine promise to increase diagnostic accuracy and streamline laboratory operations leading ...

ASAS-NANP symposium: mathematical modeling in animal nutrition-Making sense of big data and machine learning: how open-source code can advance training of animal scientists.

Journal of animal science
Advancements in precision livestock technology have resulted in an unprecedented amount of data being collected on individual animals. Throughout the data analysis chain, many bottlenecks occur, including processing raw sensor data, integrating multi...

Development of a Web Application based on Machine Learning for screening esophageal varices in cirrhosis.

La Tunisie medicale
INTRODUCTION: Esophageal varices (EV) are a common manifestation of portal hypertension in cirrhotic patients. Upper gastrointestinal endoscopy (UGE) is the gold standard for diagnosing EV. However, it is an invasive examination with a relatively hig...

Drug-Protein Interactions Prediction Models Using Feature Selection and Classification Techniques.

Current drug metabolism
BACKGROUND: Drug-Protein Interaction (DPI) identification is crucial in drug discovery. The high dimensionality of drug and protein features poses challenges for accurate interaction prediction, necessitating the use of computational techniques. Dock...

Machine learning in predicting gastric cancer survival Presenting a novel decision support system model.

Annali italiani di chirurgia
BACKGROUND: Gastric cancer is the 4th most frequent cause of cancer-related deaths, with a 5-year survival rate of less than 40%. In recent years, many artificial intelligence applications have been used in the field of gastric cancer through their e...

ToxAIcology - The evolving role of artificial intelligence in advancing toxicology and modernizing regulatory science.

ALTEX
Toxicology has undergone a transformation from an observational science to a data-rich discipline ripe for artificial intelligence (AI) integration. The exponential growth in computing power coupled with accumulation of large toxicological datasets h...

Quantitative Structure Activity/Toxicity Relationship through Neural Networks for Drug Discovery or Regulatory Use.

Current topics in medicinal chemistry
Quantitative structure - activity relationship (QSAR) modelling is widely used in medicinal chemistry and regulatory decision making. The large amounts of data collected in recent years in materials and life sciences projects provide a solid foundati...