AIMC Topic: Forensic Psychiatry

Clear Filters Showing 1 to 10 of 12 articles

Cognitive biases in forensic psychiatry: A scoping review.

International journal of law and psychiatry
Forensic psychiatry plays a critical role in legal contexts but is highly susceptible to cognitive biases that can undermine the accuracy and objectivity of evaluations. This scoping review, guided by the Arksey and O'Malley framework, aims to identi...

Artificial intelligence in insanity evaluation. Potential opportunities and current challenges.

International journal of law and psychiatry
The formulation of a scientific opinion on whether the individual who committed a crime should be held responsible for his/her actions or should be considered not responsible by reason of insanity is very difficult. Indeed, forensic psychopathologica...

Artificial intelligence and forensic mental health in Africa: a narrative review.

International review of psychiatry (Abingdon, England)
This narrative review examines the integration of Artificial Intelligence (AI) tools into forensic psychiatry in Africa, highlighting possible opportunities and challenges. Specifically, AI may have the potential to augment screening in prisons, risk...

On the Ethics and Practicalities of Artificial Intelligence, Risk Assessment, and Race.

The journal of the American Academy of Psychiatry and the Law
Artificial intelligence (AI) has been put forth as a potential means of improving and expediting violence risk assessment in forensic psychiatry. Furthermore, it has been proffered as a means of mitigating bias by replacing subjective human judgement...

Ethics Implications of the Use of Artificial Intelligence in Violence Risk Assessment.

The journal of the American Academy of Psychiatry and the Law
Artificial intelligence is rapidly transforming the landscape of medicine. Specifically, algorithms powered by deep learning are already gaining increasingly wide adoption in fields such as radiology, pathology, and preventive medicine. Forensic psyc...

Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach.

BMC psychiatry
BACKGROUND: Prolonged forensic psychiatric hospitalizations have raised ethical, economic, and clinical concerns. Due to the confounded nature of factors affecting length of stay of psychiatric offender patients, prior research has called for the app...

Risk prediction using natural language processing of electronic mental health records in an inpatient forensic psychiatry setting.

Journal of biomedical informatics
OBJECTIVE: Instruments rating risk of harm to self and others are widely used in inpatient forensic psychiatry settings. A potential alternate or supplementary means of risk prediction is from the automated analysis of case notes in Electronic Health...

RIPTOSO: The development of a screening tool for adverse events during forensic-psychiatric inpatient treatments of offenders with schizophrenia spectrum disorders.

Psychiatry research
Adverse events such as compulsory measures, absconding, illicit substance use, self-harm, aggressive behavior, and prolonged hospitalization pose significant challenges in forensic psychiatric inpatient care. This study introduces a machine learning-...

Artificial intelligence in forensic mental health: A review of applications and implications.

Journal of forensic and legal medicine
This narrative review explores the transformative role of artificial intelligence (AI) in forensic mental health, focusing on its applications, benefits, limitations, and ethical considerations. AI's capabilities, particularly in areas such as risk a...

AI-Assisted Deception and the Emerging Challenge of LLMs in Forensic Psychiatry.

The journal of the American Academy of Psychiatry and the Law
Generative artificial intelligence (AI), including the large language model ChatGPT, has introduced potential new opportunities and challenges to the practice of forensic psychiatry. These powerful AI-based tools may offer substantial benefits in adm...