Qualitative analysis of blood from patients engaging in deliberate self-harm: Differences between prescribed and detected drugs.

Background: While drugs are sometimes taken during deliberate self-harm (DSH), no study has attempted to analyze drugs in the blood of DSH patients and compare them with prescribed medications or other drugs. In this study, drugs were analyzed from the blood of DSH patients, and the detected, prescribed, and suspected drugs were documented.

Methods: Patients who practiced DSH and were transferred to the emergency sites of Fukuoka University Hospital between April 2021 and September 2022 participated in the study.

Sex estimation using skull silhouette images from postmortem computed tomography by deep learning.

Prompt personal identification is required during disasters that can result in many casualties. To rapidly estimate sex based on skull structure, this study applied deep learning using two-dimensional silhouette images, obtained from head postmortem computed tomography (PMCT), to enhance the outline shape of the skull. We investigated the process of sex estimation using silhouette images viewed from different angles and majority votes.

Gray-Scale Extraction of Bone Features from Chest Radiographs Based on Deep Learning Technique for Personal Identification and Classification in Forensic Medicine.

Post-mortem (PM) imaging has potential for identifying individuals by comparing ante-mortem (AM) and PM images. Radiographic images of bones contain significant information for personal identification. However, PM images are affected by soft tissue decomposition; therefore, it is desirable to extract only images of bones that change little over time.

Survey of psychiatric symptoms among inpatients with COVID-19 using the Diagnosis Procedure Combination data and medical records in Japan.

Physical symptoms such as fatigue and muscle weakness, and psychiatric symptoms like depression and anxiety are considered as complications and sequelae of COVID-19. This epidemiological study investigated the actual status of psychiatric symptoms and disorders caused by COVID-19, from four major university hospitals and five general hospitals in Fukuoka Prefecture, Japan, having a population of 5 million. We conducted a survey of psychiatric disorders associated with COVID-19 using Diagnosis Procedure Combination (DPC) data and the psychiatric records of the hospitals.

Development of an artificial intelligence-based algorithm to classify images acquired with an intraoral scanner of individual molar teeth into three categories.

Background: Forensic dentistry identifies deceased individuals by comparing postmortem dental charts, oral-cavity pictures and dental X-ray images with antemortem records. However, conventional forensic dentistry methods are time-consuming and thus unable to rapidly identify large numbers of victims following a large-scale disaster.

Objective: Our goal is to automate the dental filing process by using intraoral scanner images.