Machine learning has revolutionised the field of classification in numerous domains, providing robust tools for categorising data into discrete classes. However, many practical applications, such as ...

Assessing Algorithmic Fairness With a Multimodal Artificial Intelligence Model in Men of African and Non-African Origin on NRG Oncology Prostate Cancer Phase III Trials Recent advances in machine ...

Please provide your email address to receive an email when new articles are posted on . A machine learning classifier was trained on capnogram features. The model’s probability output inversely ...

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry ...

• Repurposed COVID-19 RATs provide an ideal platform for observing differences in blood coagulability. • Random Forest image classification algorithms can facilitate rapid coagulation status ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Lyme disease is a high-incidence infectious disease with a global prevalence of 14.5% of the world's population. Two-tier serology is currently the primary diagnostic test for Lyme disease; however, ...

Machine learning identifies HLA structural features linked to graft failure, improving prediction and donor selection in ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

A recent study explored rapid evaporative ionization mass spectrometry (REIMS) as a high-throughput, real-time alternative. By analyzing metabolomic fingerprints from pig neck fat, REIMS was combined ...