AIMC Topic: London

Clear Filters Showing 21 to 29 of 29 articles

Evaluating clustering methods within the Artificial Ecosystem Algorithm and their application to bike redistribution in London.

Bio Systems
This paper proposes and evaluates a solution to the truck redistribution problem prominent in London's Santander Cycle scheme. Due to the complexity of this NP-hard combinatorial optimisation problem, no efficient optimisation techniques are known to...

Population pharmacokinetic/pharmacodynamic assessment of pharmacological effect of a selective estrogen receptor β agonist on total testosterone in healthy men.

Clinical pharmacology in drug development
BACKGROUND: LY500307 is a highly selective estrogen receptor β (ERβ) agonist, which loses its selectivity at high dose and leads to undesirable suppression of total testosterone (TT) concentration. The objective of the present analysis was to define ...

Using Artificial Intelligence and Machine Learning to Promote Child Health Equity.

Pediatrics
Artificial intelligence (AI) and machine learning (ML), used injudiciously, have the potential to exacerbate health inequalities. Conversely, there is a potential to use ML to give insight into the impact of socioeconomic factors, which allows us to ...

Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.

Annals of family medicine
PURPOSE: Increased workload associated with electronic visits (eVisits) in primary care could potentially be decreased by the use of artificial intelligence (AI); however, it is unknown whether this use of AI would be acceptable to staff and patients...

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Schizophrenia bulletin
BACKGROUND: Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis.

Validation of artificial neural networks as a methodology for donor-recipient matching for liver transplantation.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
In 2014, we reported a model for donor-recipient (D-R) matching in liver transplantation (LT) based on artificial neural networks (ANNs) from a Spanish multicenter study (Model for Allocation of Donor and Recipient in España [MADR-E]). The aim is to ...