Severe acute malnutrition morphological patterns in children under five

Medialdea, Laura; Bogin, Barry; Thiam, Mbeugué; Vargas, Antonio; Marrodán, María Dolores; Idohou-Dossou, Nicole

doi:10.1038/s41598-021-82727-x

Cited by 7 publications

(6 citation statements)

References 32 publications

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“…These efforts include the neural operator learning approach, which aims to learn the mappings between dynamic system inputs and system states ( Medialdea et al, 2021 ). The network may operate as a replacement for a solution operator in a dynamic system, and DBP-DIT is especially interesting ( Heddleston et al, 2021 ).…”

Section: Summary Of Digital Image Technologymentioning

confidence: 99%

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Chen

et al. 2022

Front. Genet.

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Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today’s microscopes can capture digital images. A light microscope is an essential tool in biology and medicine. Analyzing the generated images will involve the creation of unique analytical techniques. Digital images of the material before and after deformation can be compared to assess how much strain and displacement the material responds. Furthermore, this article proposes Development Biology Patterns using Digital Image Technology (DBP-DIT) to cell image data in 2D, 3D, and time sequences. Engineered materials with high stiffness may now be characterized via digital image correlation. The proposed method of analyzing the mechanical characteristics of skin under various situations, such as one direction of stress and temperatures in the hundreds of degrees Celsius, is achievable using digital image correlation. A DBP-DIT approach to biological tissue modeling is based on digital image correlation (DIC) measurements to forecast the displacement field under unknown loading scenarios without presupposing a particular constitutive model form or owning knowledge of the material microstructure. A data-driven approach to modeling biological materials can be more successful than classical constitutive modeling if adequate data coverage and advice from partial physics constraints are available. The proposed procedures include a wide range of biological objectives, experimental designs, and laboratory preferences. The experimental results show that the proposed DBP-DIT achieves a high accuracy ratio of 99,3%, a sensitivity ratio of 98.7%, a specificity ratio of 98.6%, a probability index of 97.8%, a balanced classification ratio of 97.5%, and a low error rate of 38.6%.

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Section: Summary Of Digital Image Technologymentioning

confidence: 99%

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Chen

et al. 2022

Front. Genet.

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“…Many patterns of growth, development, and treatment changes may be observed with high precision using anthropometry. [1] Craniofacial anthropometry has aided in the diagnosis and follow-up of diseases such as Down syndrome, Cushing syndrome, Celiac disease, Addison disease, and Horner syndrome. [2] It is employed in industrial design of products like head gear and face masks [3].…”

Section: Introductionmentioning

confidence: 99%

Craniofacial Angular Photogrammetric Evaluation of Ijaws Resident in Port Harcourt, Nigeria

Fawehinmi,

Okoh,

Oghenemavwe

et al. 2023

JAMMR

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Aim: Evaluation of facial angles is essential for defining facial traits in clinical and population studies. The aim of this research was to quantify the normative values of craniofacial angular parameters in Ijaws using a photogrammetric approach. Methodology: The study employed a cross-sectional design involving 300 (150 males and 150 females) persons of Ijaw extraction between the ages of 18 to 40 years. Frontal and lateral view photographs of each subject were taken in the Natural Head Position and analyzed using Pro-Image Facial Software to evaluate nine angular facial parameters. Data were analyzed using SPSS version 25. Results and Discussion: The mean value Nasofrontal (NFA), Nasolabial (NLA), Nasofacial (NFCA), Nasomemtal (NMA), Mentocervical (MCA) angles, were 158.36±95.86º, 127.49±37.68 º, 34.27±12.72 º, 135.63±33.77 º, 88.38±20.26 º respectively. Males had a mean value of NFA, NLA, NFCA, NMA and MCA 154.02±20.90º, 137.00±32.97º, 39.14±19.00º, 122.59±45.2º, 86.93±29.66º respectively while females are 162. 69±134.03º 117.98±39.76º, 31.28±4.26º, 143.79±20.29 º, 89.41±8.9º respectively. NLA, NFC and NMA were statistically significant P <0.05. The study demonstrated some similarities and differences in angular craniofacial parameters of Ijaws residing in Port Harcourt when compared to other related studies. Variations observed could be attributed to nationality, ethnicity and race. There was sexual dimorphism in nasolabial, nasofacial and nasomental angles. Age-related difference was observed in nasolabial angle while nasofrontal, nasomental and nasofacial have no age differences. Conclusion: This study shows that the normative facial angles of Ijaws residing in Port Harcourt were higher compared to those of the Caucasians, and neighboring ethnicities. There was sexual dimorphism in nasolabial, nasofacial, nasomental, only nasolabial showed significant difference with age. The findings of this study will be useful in industrial designs, ergonomics, maxillofacial surgery and facial reconstruction.

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“…Preliminary validation studies for software aiming to directly classify acute malnutrition have encountered methodological as well as logistic challenges. The Photo Diagnosis App validation phase study in Spain and Senegal found high accuracy of diagnosis but suggested significant morphometric differences among the populations sampled, implying a need to investigate this morphological variability [ 5 , 6 ]. The researchers involved in the study noted that, although morphological variability could likely be overcome with machine learning, the approach proved very expensive compared with current technologies and that capturing a viable scan required conditions that could not be repeated in the field (AV Brizuela, personal communication, February 25, 2022).…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan

Leidman¹,

Jatoi²,

Bollemeijer³

et al. 2022

JMIR Biomed Eng

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Background Adoption of 3D imaging systems in humanitarian settings requires accuracy comparable with manual measurement notwithstanding additional constraints associated with austere settings. Objective This study aimed to evaluate the accuracy of child stature and mid–upper arm circumference (MUAC) measurements produced by the AutoAnthro 3D imaging system (third generation) developed by Body Surface Translations Inc. Methods A study of device accuracy was embedded within a 2-stage cluster survey at the Malakal Protection of Civilians site in South Sudan conducted between September 2021 and October 2021. All children aged 6 to 59 months within selected households were eligible. For each child, manual measurements were obtained by 2 anthropometrists following the protocol used in the 2006 World Health Organization Child Growth Standards study. Scans were then captured by a different enumerator using a Samsung Galaxy 8 phone loaded with a custom software, AutoAnthro, and an Intel RealSense 3D scanner. The scans were processed using a fully automated algorithm. A multivariate logistic regression model was fit to evaluate the adjusted odds of achieving a successful scan. The accuracy of the measurements was visually assessed using Bland-Altman plots and quantified using average bias, limits of agreement (LoAs), and the 95% precision interval for individual differences. Key informant interviews were conducted remotely with survey enumerators and Body Surface Translations Inc developers to understand challenges in beta testing, training, data acquisition and transmission. Results Manual measurements were obtained for 539 eligible children, and scan-derived measurements were successfully processed for 234 (43.4%) of them. Caregivers of at least 10.4% (56/539) of the children refused consent for scan capture; additional scans were unsuccessfully transmitted to the server. Neither the demographic characteristics of the children (age and sex), stature, nor MUAC were associated with availability of scan-derived measurements; team was significantly associated (P<.001). The average bias of scan-derived measurements in cm was −0.5 (95% CI −2.0 to 1.0) for stature and 0.7 (95% CI 0.4-1.0) for MUAC. For stature, the 95% LoA was −23.9 cm to 22.9 cm. For MUAC, the 95% LoA was −4.0 cm to 5.4 cm. All accuracy metrics varied considerably by team. The COVID-19 pandemic–related physical distancing and travel policies limited testing to validate the device algorithm and prevented developers from conducting in-person training and field oversight, negatively affecting the quality of scan capture, processing, and transmission. Conclusions Scan-derived measurements were not sufficiently accurate for the widespread adoption of the current technology. Although the software shows promise, further investments in the software algorithms are needed to address issues with scan transmission and extreme field contexts as well as to enable improved field supervision. Differences in accuracy by team provide evidence that investment in training may also improve performance.

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Severe acute malnutrition morphological patterns in children under five

Cited by 7 publications

References 32 publications

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Craniofacial Angular Photogrammetric Evaluation of Ijaws Resident in Port Harcourt, Nigeria

Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan

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