Machine learning (ML) is a powerful tool that delivers insights hidden in Internet of Things
(IoT) data. These hybrid technologies work smartly to improve the decision-making process …

In the modern history of psychotherapy, understanding the individual patient and how to
optimize treatment for each individual has been an important challenge. For the therapist …

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of
COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the …

Most machine learning-based methods predict outcomes rather than understanding
causality. Machine learning methods have been proved to be efficient in finding correlations …

This introductory chapter to the seventh and 50-year anniversary edition of Bergin and
Garfield's Handbook of Psychotherapy and Behavior Change provides a context for current …

While the evidence on the effectiveness of different psychotherapies is often strong, it is not
settled whereby and how these therapies work. Knowledge on the causal factors and …

BackgroundSuicide prediction models have been formulated in a variety of ways and are
heterogeneous in the strength of their predictions. Machine learning has been a proposed …

This article presents a systematic literature review that expands and updates a previous
review on the application of machine learning to laboratory medicine. We used Scopus and …

The early development of cognitive behavior therapy (CBT) can be characterized by the
coming together of behavioral and cognitive traditions. However, the past decades have …

Background: With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it
has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to …