Artificial Intelligence in Evaluation of Permanent Impairment: New Operational Frontiers

Abstract

Artificial intelligence (AI) and machine learning (ML) span multiple disciplines, including the medico-legal sciences, also with reference to the concept of disease and disability. In this context, the International Classification of Diseases, Injuries, and Causes of Death (ICD) is a standard for the classification of diseases and related problems developed by the World Health Organization (WHO), and it represents a valid tool for statistical and epidemiological studies. Indeed, the International Classification of Functioning, Disability, and Health (ICF) is outlined as a classification that aims to describe the state of health of people in relation to their existential spheres (social, family, work). This paper lays the foundations for proposing an operating model for the use of AI in the assessment of impairments with the aim of making the information system as homogeneous as possible, starting from the main coding systems of the reference pathologies and functional damages. Providing a scientific basis for the understanding and study of health, as well as establishing a common language for the assessment of disability in its various meanings through AI systems, will allow for the improvement and standardization of communication between the various expert users.

A machine learning-based predictive model of causality in orthopaedic medical malpractice cases in China

“…We summarized the previous literature reports [14,[25][26][27][28][29][30][31], after fully understanding those common factors and considering the reality of medical malpractice cases in China, and divided the influencing factors on the degree of causality into medical factors (91 technical faults and 29 non-technical faults) and 10 patient factors (S1 Table ). Regarding the attribution of medical malpractice, it is generally observed that an increased number of affirmative responses in medical factors correlates with a higher degree of hospital liability in the case.…”

“…In forensic odontology, AI has been utilized to forecast age and gender from dental characteristics, facilitating both human identification processes and the analysis of bite marks [ 13 ]. In disability assessment, researchers have tried to combine ML with the International Classification of Functioning, Disability, and Health (ICF) to assess the degree of disability more accurately and conveniently [ 14 , 15 ]. In addition, ML also has some applications in forensic pathology, forensic genetics and other forensic branches.…”