Forensic Case Identification

INTRODUCTION: Tongue is a vital internal organ enclosed within the oral cavity and is well protected from the external environment. The color, shape, and surface features are characteristic of every individual, and this serves as a tool for identification. The search for a new personal identification method secure has led to the use of the tongue print as a method of biometric verification.AIM AND OBJECTIVE: To analyze the shape, margins, texture of tongue prints and compare these between males and females. Also, formulate a working classification system for these tongue prints.MATERIAL AND METHODS: Subjects were asked to protrude tongue in relaxed position. After this tongue images were captured using Nikon digital camera to evaluate the shape, texture, margins, and papillations of tongue patterns.RESULT: The most common pattern seen in males and females was Patternless, with majority of subjects showing scalloped lateral margins, prominent papillations with short and broad tongue. Mostly female patients had pointed tip of tongue. Also, we in this paper have formulated a working classification system for easily categorizing the tongue print patterns in individuals.CONCLUSION: The human tongue is unique and delivers relevant information about shape, size, color, texture, margins and is suitable for forensic case identification.

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Dissociative identity disorder (DID) in japan: A forensic case report and the recent increase in reports of DID

International Journal of Psychiatry in Clinical Practice ◽

10.3109/13651500009178003 ◽

2000 ◽

Vol 4 (2) ◽

pp. 155-160 ◽

Cited By ~ 2

Author(s):

Yukio Uchinuma ◽

Yoshio Sekine

Keyword(s):

Case Report ◽

Dissociative Identity Disorder ◽

Recent Increase ◽

Forensic Case

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Faculty Opinions recommendation of Hepatitis C virus testing for case identification in persons born during 1945-1965: Results from three randomized controlled trials.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.731259659.793553784 ◽

2018 ◽

Author(s):

Norah Terrault

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Randomized Controlled Trials ◽

Controlled Trials ◽

Case Identification ◽

Randomized Controlled ◽

Virus Testing

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Alpha-Pyrrolidinopentiothiophenone (α-PVT): A forensic case study including plasma concentrations

Forensic Science International ◽

10.1016/j.forsciint.2021.110721 ◽

2021 ◽

Vol 321 ◽

pp. 110721

Author(s):

Liane D. Paul ◽

Jessica Welter-Luedeke ◽

Saskia Penzel ◽

Anna Zangl ◽

Matthias Graw

Keyword(s):

Plasma Concentrations ◽

Forensic Case

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Assisting scalable diagnosis automatically via CT images in the combat against COVID-19

Scientific Reports ◽

10.1038/s41598-021-83424-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Bohan Liu ◽

Pan Liu ◽

Lutao Dai ◽

Yanlin Yang ◽

Peng Xie ◽

...

Keyword(s):

Large Scale ◽

Area Under The Curve ◽

Independent Set ◽

Reference Method ◽

Ct Images ◽

Loss Of Life ◽

Case Identification ◽

Reverse Transcription Pcr ◽

Using Data

AbstractThe pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

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Impact of maternal thyroid disease on neonatal thyroid status

Journal of Pediatric Endocrinology and Metabolism ◽

10.1515/jpem-2020-0349 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Lakshmi Venugopalan ◽

Aishwarya Rajan ◽

Hemchand. K. Prasad ◽

Anupama Sankaran ◽

Gnanabalan Murugesan ◽

...

Keyword(s):

Congenital Hypothyroidism ◽

Thyroid Stimulating Hormone ◽

Study Group ◽

Thyroid Status ◽

Case Identification ◽

Group I ◽

Group Ii ◽

Maternal Thyroid ◽

Heel Prick ◽

Stimulating Hormone

AbstractObjectivesPrevalence of Maternal and congenital hypothyroidism is on the rise. To present the thyroid stimulating hormone screening results in babies born to hypothyroid mothers and assess the burden, aetiology of hypothyroidism in these babiesMethodsAll antenatal mothers attending our hospital during the study period were enrolled into the study. Group I includes 249 term babies born to hypothyroid mothers and group II comprises 2154 newborns born to mothers who are euthyroid. Heel prick thyroid stimulating hormone was done for all newborns on day 3 for both groups. Confirmatory venous testing was done for all for babies in group I and screen positives belonging to group II. Evaluation and therapy done as per standard guidelines.ResultsThyroid stimulating hormone values in the two groups are presented. There was significant correlation between peak maternal thyroid stimulating hormone and neonatal day 3 heel prick in group I (r=0.7, P<0.05). The prevalence of positive screening test in groups I and II was 3.8 and 1.03% (p<0.05) whereas corresponding values for confirmed disease was 4.3 and 0.6%, respectively (p<0.05). Aetiological evaluation revealed both transient hypothyroidism (33.3%) and permanent hypothyroidism (66.6%).Conclusion4.3% of babies born to hypothyroid mothers develop congenital hypothyroidism; aetiology being both transient and permanent. A venous test by 3 weeks is helpful in these babies to improve case identification.

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