Researchers made a technique that improves the trustworthiness of machine-learning models, which could help improve the accuracy and reliability of AI predictions for high-stakes settings such health ...

An artificial intelligence (AI) model improved outcomes in hospitalized patients by quadrupling the rate of detection and ...

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs ...

Genetic algorithms can automate data preparation, feature selection, and hyperparameter tuning in machine learning. Learn to ...

Sarat Kiran highlights a pivotal shift in supply chain evolution where data, intelligence, and automation converge ...

The powerful chemotherapy drug cisplatin has been used since the late 1970s to treat a variety of cancers. It's highly ...

Researchers from Rice University (TX, USA) have developed a new machine learning algorithm that interprets optical spectra of ...

The study underscores that traditional statistical approaches, while valuable, often fail to capture the intricate relationships between environmental, temporal, and situational factors leading to ...

More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care.

Patients are compared to each other using multivariate time series (MTS) data. Each ICU patient's stay is represented as a ...

Researchers pioneered the integration of CNN-LSTM with bond stress-slip constitutive modeling and proposed a deep ...