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1.
Am J Forensic Med Pathol ; 42(4): e67-e68, 2021 Dec 01.
Artículo en Inglés | MEDLINE | ID: mdl-33989207

RESUMEN

ABSTRACT: Intestinal perforation is an uncommon complication and presentation of verocytotoxigenic Escherichia coli (VTEC) infection in individuals with Prader-Willi syndrome (PWS). The common site of perforation from VTEC infection is in the colon (and almost exclusively in the pediatric population), whereas PWS is in the stomach. Terminal ileum perforation is uncommon and is not reported in either these 2 conditions. We report a death from terminal ileum perforations in an adult who had PWS and was infected with VTEC. Potential reasons why the perforation occurred at this rare location, rather than in other more common location, in an adult are discussed.


Asunto(s)
Infecciones por Escherichia coli , Síndrome de Prader-Willi , Adulto , Niño , Infecciones por Escherichia coli/complicaciones , Humanos , Íleon , Síndrome de Prader-Willi/complicaciones
2.
Am J Forensic Med Pathol ; 42(3): 230-234, 2021 Sep 01.
Artículo en Inglés | MEDLINE | ID: mdl-33833193

RESUMEN

ABSTRACT: Convolutional neural network (CNN) has advanced in recent years and translated from research into medical practice, most notably in clinical radiology and histopathology. Research on CNNs in forensic/postmortem pathology is almost exclusive to postmortem computed tomography despite the wealth of research into CNNs in surgical/anatomical histopathology. This study was carried out to investigate whether CNNs are able to identify and age myocardial infarction (a common example of forensic/postmortem histopathology) from histology slides. As a proof of concept, this study compared 4 CNNs commonly used in surgical/anatomical histopathology to identify normal myocardium from myocardial infarction. A total of 150 images of the myocardium (50 images each for normal myocardium, acute myocardial infarction, and old myocardial infarction) were used to train and test each CNN. One of the CNNs used (InceptionResNet v2) was able to show a greater than 95% accuracy in classifying normal myocardium from acute and old myocardial infarction. The result of this study is promising and demonstrates that CNN technology has potential applications as a screening and computer-assisted diagnostics tool in forensic/postmortem histopathology.


Asunto(s)
Patologia Forense/métodos , Infarto del Miocardio/clasificación , Infarto del Miocardio/patología , Miocardio/patología , Redes Neurales de la Computación , Fibroblastos/patología , Fibrosis , Hemorragia/patología , Humanos , Procesamiento de Imagen Asistido por Computador , Miocitos Cardíacos/patología , Neutrófilos/metabolismo
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