Algorithms for Empathy: Using Machine Learning to Categorize Common Empathetic Traits Across Professional and Peer-Based Conversations.

Introduction In this article, we describe our creation of a machine-learning model that uses a combination of rule-based and natural language processing (NLP) algorithms. We show how this "Empathy Algorithm" was developed and how its results compare to three datasets of professional counseling and peer-led conversations.  Methods These conversation datasets were rated by people with varying degrees of empathetic expertise (from counselors to student volunteers) and labeled as either low- or high-quality empathy.

Environmental and policy approaches to cardiovascular disease prevention through physical activity: issues and opportunities.

The majority of Americans remain inactive despite evidence of significant health benefits from even moderately intense activity. Previous intervention efforts have generally focused on changing individual behavior. This article discusses the use of policy, legislative and regulatory, and environmental interventions in promoting physical activity to prevent cardiovascular disease (CVD) and other chronic diseases.

A custody and placement evaluation of an infant with a psychotic, mentally retarded mother.

An emergency evaluation was requested on a 16-week-old infant and her parents. The child's mother had a long history of schizophrenia and mental retardation and was noted to decompensate following the child's birth; the mother was hospitalized and the child placed in foster care. Although the mother was severely impaired, the family had a reasonable and appropriate plan for the infant's care and reunification of the family was recommended.