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Drowning

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Digital whole-slide image analysis for automated diatom test in forensic cases of drowning using a convolutional neural network algorithm.

Forensic science international
Diatom examinations have been widely used to perform drowning diagnosis in forensic practice. However, current methods for recognizing diatoms, which use light or electron microscopy, are time-consuming and laborious and often result in false positiv...

Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases.

Fa yi xue za zhi
Objective To discuss the application of artificial intelligence automatic diatom identification system in practical cases, to provide reference for quantitative diatom analysis using the system and to validate the deep learning model incorporated int...

Automated diatom searching in the digital scanning electron microscopy images of drowning cases using the deep neural networks.

International journal of legal medicine
Forensic diatom test has been widely accepted as a way of providing supportive evidences in the diagnosis of drowning. The current workflow is primarily based on the observation of diatoms by forensic pathologists under a microscopy, and this process...

An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm.

International journal of legal medicine
Seasonal or monthly databases of the diatom populations in specific bodies of water are needed to infer the drowning site of a drowned body. However, existing diatom testing methods are laborious, time-consuming, and costly and usually require specif...

Deep Learning and 5G and Beyond for Child Drowning Prevention in Swimming Pools.

Sensors (Basel, Switzerland)
Drowning is a major health issue worldwide. The World Health Organization's global report on drowning states that the highest rates of drowning deaths occur among children aged 1-4 years, followed by children aged 5-9 years. Young children can drown ...

A 2.5D Deep Learning-Based Method for Drowning Diagnosis Using Post-Mortem Computed Tomography.

IEEE journal of biomedical and health informatics
It is challenging to diagnose drowning in autopsy even with the help of post-mortem multi-slice computed tomography (MSCT) due to the complex pathophysiology and the shortage of forensic specialists equipped with radiology knowledge. Therefore, a com...

Surface and underwater human pose recognition based on temporal 3D point cloud deep learning.

Scientific reports
Airborne surface and underwater human pose recognition are crucial for various safety and surveillance applications, including the detection of individuals in distress or drowning situations. However, airborne optical cameras struggle to achieve simu...

Inconsistency between Human Observation and Deep Learning Models: Assessing Validity of Postmortem Computed Tomography Diagnosis of Drowning.

Journal of imaging informatics in medicine
Drowning diagnosis is a complicated process in the autopsy, even with the assistance of autopsy imaging and the on-site information from where the body was found. Previous studies have developed well-performed deep learning (DL) models for drowning d...

Integrating microbial profiling and machine learning for inference of drowning sites: a forensic investigation in the Northwest River.

Microbiology spectrum
Drowning incidents present significant challenges for forensic investigators in determining the exact site of occurrence. Traditional forensic methods often rely on physical evidence and circumstantial clues, but the emerging field of forensic microb...