Algorithm of Death: Types, Navigating Boundary of Life, Disposition Methods, AI Death Determination, Modern Science of Mortality in India and World, Post-Mortem, Taphonomy, Thanatological Control, Forensic Pathology

Abstract

Death is a complex biological, medical, forensic, and social phenomenon that has evolved from traditional clinical assessment to a multidisciplinary field integrating artificial intelligence (AI), forensic pathology, post-mortem sciences, taphonomy, thanatology, and mortality surveillance systems. This review examines the major types of death and the increasingly complex boundary between life and death, highlighting advances in death determination, mortality prediction, forensic investigations, and human remains management. Particular attention is given to the role of AI in mortality risk prediction, cause-of-death classification, clinical decision support, and public health monitoring. The review further explores contemporary developments in forensic pathology, autopsy science, taphonomic research, and thanatological studies, emphasizing their contributions to understanding post-mortem processes and death-related practices. Findings from the reviewed literature indicate that emerging technologies such as machine learning, virtual autopsy, molecular diagnostics, and digital health systems have significantly improved the accuracy, efficiency, and reliability of death investigation and mortality assessment. Despite these advancements, challenges related to data quality, technological accessibility, ethical concerns, and the need for standardized protocols remain.