At a STAT Summit, discussion of health insurers' use of algorithms to predict how long patients need intense care — and how that affects families.

Artificial Intelligence 'Murder prediction' algorithms echo some of Stalin's most horrific policies — governments are treading a very dangerous line in pursuing them ...

Prediction of Patients With High-Risk Osteosarcoma on the Basis of XGBoost Algorithm Using Transcriptome and Methylation Data From SGH-OS Cohort. If you have the appropriate software installed, you ...

Genetic algorithms evaluate potential solutions by evolving them over many generations and keeping the ones which work best each time.

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

The diabetes prediction system is designed to predict the risk of diabetes utilizing clinical and genetic information through deep learning artificial intelligence algorithms.

The study has several limitations, with future work needed to improve reliability of inference from observational data from biobanks and to understand the limitations of genetic risk prediction.

In this paper, we present a machine learning classifier which is used for pedestrian detection based on XGBoost. Our approach, the Genetic Algorithm is introduced to optimize the parameter tuning ...

Luke Fox: The goal of using the genetic algorithm was to create an optimal massing that prioritized the creation of a central public square and maximized views for the building's occupants.

A new advanced artificial intelligence (AI) algorithm more accurately model how genes associated with specific autoimmune diseases are expressed and regulated and to identify additional genes of ...