AIMC Topic: Artificial Intelligence

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Artificial Intelligence and Machine Learning for Lead-to-Candidate Decision-Making and Beyond.

Annual review of pharmacology and toxicology
The use of artificial intelligence (AI) and machine learning (ML) in pharmaceutical research and development has to date focused on research: target identification; docking-, fragment-, and motif-based generation of compound libraries; modeling of sy...

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review.

Sensors (Basel, Switzerland)
Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential ...

Emerging Artificial Intelligence-Empowered mHealth: Scoping Review.

JMIR mHealth and uHealth
BACKGROUND: Artificial intelligence (AI) has revolutionized health care delivery in recent years. There is an increase in research for advanced AI techniques, such as deep learning, to build predictive models for the early detection of diseases. Such...

The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence.

Animal health research reviews
Livestock welfare assessment helps monitor animal health status to maintain productivity, identify injuries and stress, and avoid deterioration. It has also become an important marketing strategy since it increases consumer pressure for a more humane...

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis.

PloS one
There is a dearth of literature that provides a bibliometric analysis concerning the role of Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this research gap and provides evidence from the studies conduc...

High-throughput whole-slide scanning to enable large-scale data repository building.

The Journal of pathology
Digital pathology and artificial intelligence (AI) rely on digitization of patient material as a necessary first step. AI development benefits from large sample sizes and diverse cohorts, and therefore efforts to digitize glass slides must meet these...