Insights from explainable AI in oesophageal cancer team decisions.

Background: Clinician-led quality control into oncological decision-making is crucial for optimising patient care. Explainable artificial intelligence (XAI) techniques provide data-driven approaches to unravel how clinical variables influence this decision-making. We applied global XAI techniques to examine the impact of key clinical decision-drivers when mapped by a machine learning (ML) model, on the likelihood of receiving different oesophageal cancer (OC) treatment modalities by the multidisciplinary team (MDT).

Factors that distinguish aggression toward animals from other antisocial behaviors: Evidence from a community sample.

Animal cruelty is a form of passive and active aggression that is largely undocumented and unreported. Given that animals are voiceless victims, we have to rely on witnesses and frontline staff (e.g.

Not the Sum of Its Parts: A Critical Review of the MacDonald Triad.

The MacDonald triad posits that animal cruelty, fire setting, and bed wetting in childhood is indicative of later aggressive and violent behavior in adults. Researchers refer to this phenomenon as a precursor to later antisocial behaviors including serial and sexual murder; while practitioners cite the triad in clinical formulations and risk assessments. However, there is yet to be a critical review and consolidation of the literature that establishes whether there is empirical support.

Adult-Perpetrated Animal Abuse: A Systematic Literature Review.

Adults perpetrate the majority of animal abuse incidents yet clinicians are left with very little evidence base to advance/enhance their practice. The purpose of this systematic review is to synthesize and evaluate the current literature on adult-perpetrated animal abuse and to identify the etiological factors related to this type of offending. Twenty-three studies met the specific inclusion criteria but most importantly, they examined the characteristics of adult perpetrators of animal abuse.