For the last 10 years and after important discoveries such as DNA sequence of the entire
human genome, there has been a considerable increase in the interest on researches risk …

Background: Artificial intelligence (AI) is the way to model human intelligence to accomplish
certain tasks without much intervention of human beings. The term AI was first used in 1956 …

New computational methods have emerged through science and technology to support the
diagnosis of mental health disorders. Predictive models developed from machine learning …

Classifying pan-cancer samples using gene expression patterns is a crucial challenge for
the accurate diagnosis and treatment of cancer patients. Machine learning algorithms have …

One of the forces driving science and industry is machine learning, but the proliferation of
Big Data necessitates paradigm shifts from conventional approaches in applying machine …

Outcome-wide analysis can offer several benefits, including increased power to detect weak
signals and the ability to identify exposures with multiple effects on health, which may be …

Background A growing body of literature has detailed the use of qualitative analyses to
measure the therapeutic processes and intrinsic effectiveness of psychotherapies, which …

Background: Linking genotypic changes to phenotypic traits based on machine learning
methods has various challenges. In this study, we developed a workflow based on …

Background: Gangstalking refers to a novel persecutory belief system wherein sufferers
believe that they are being followed, watched, and harassed by a vast network of people in …

Motivation In multi-cohort machine learning studies, it is critical to differentiate between
effects that are reproducible across cohorts and those that are cohort-specific. Multi-task …