In recent years, the use of artificial intelligence (AI) in health care has risen steadily,
including a wide range of applications in the field of pharmacology. AI is now used …

Identifying patient cohorts meeting the criteria of specific phenotypes is essential in
biomedicine and particularly timely in precision medicine. Many research groups deliver …

Over the past 70 years, the study of lipid metabolism has led to important discoveries in
identifying the underlying mechanisms of chronic diseases. Advances in the use of stable …

Personalized medicine, medication discovery, and development might all benefit greatly
from AI's incorporation into pharmacokinetics and pharmacodynamics. Target identification …

Explainable Artificial Intelligence (XAI) is a field that develops ways to explain predictions
made by AI models. In this paper XAI which is a multifaceted approach is discussed which is …

Simple Summary The heterogeneity of complicated diseases like cancer negatively affects
patients' responses to treatment. Finding homogeneous subgroups of patients within the …

Medication recommendation aims to provide clinicians with safe medicine combinations for
the treatment of patients. Existing medication recommendation models are built based on …

Background–Subgroup discovery (SGD) is the automated splitting of the data into complex
subgroups. Various SGD methods have been applied to the medical domain, but none have …

Drug repositioning holds great promise because it can reduce the time and cost of new drug
development. While drug repositioning can omit various R&D processes, confirming …

Subgroup discovery (SD) is a data mining technique that allows us to obtain the properties
of each element given a particular population; these properties are of interest for a specific …