Detection of Neonatal Jaundice by Using an Android OS-Based Smartphone Application

Padidar, Pouria; Shaker, Mohammadamin; Amoozgar, Hamid; Khorraminejad-Shirazi, Mohammadhossein; Hemmati, Fariba; Najib, Khadijeh Sadat; Pourarian, Shahnaz

doi:10.5812/ijp.84397

Cited by 29 publications

(32 citation statements)

References 13 publications

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“…Reviewing the recent literature, it is notable that technology is becoming an important part of medical practice from diagnosis to treatment. One of the useful aspects of technology in MS patients has been the use of social networks, for a better support in health-related coping, social interactions, and patient informing processes [21][22][23].…”

Section: Discussionmentioning

confidence: 99%

The impact of social media use on depression in multiple sclerosis patients

et al. 2020

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Social media is a powerful tool in providing information and support for minority groups such as patients with chronic diseases. We aimed to assess the link between using online social media and depression in a sample population of Iranian Multiple Sclerosis (MS) patients. In this cross-sectional study, a number of MS patients between 18-55 years were recruited. The Persian-language version of the Beck Depression Inventory-II (BDI-II-Persian) was used to screen MS patients for depression. We selected a cutoff point of 16 to identify depressed MS patients, who answered the self-administered questionnaire designed by the authors (the validity and reliability was confirmed before). Patients, whose interaction with social networks and communication tools was limited to < 1 h/day for < 5 times/month, were allocated as controls. A two-sided p < 0.05 was considered statistically significant. We compared the depression score between patients who used internet and social media (16.38 ± 8.35) with those who did not (25 ± 13.98). We found out there was a significant difference (p = 0.046). However, there were no significant differences between the type (r = 0.098, p = 0.513) and duration (r = − 0.102, p = 0.564) of social media with depression score. Also, based on a cutoff of 3 number of social media there was no significant difference in the status of depression among patients (p = 0.921). Based on the experience of patients, it is helpful to implement a source using online social media to facilitate patients' access to rehabilitation support and establish support groups with standard supervised information delivery.

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Section: Discussionmentioning

confidence: 99%

The impact of social media use on depression in multiple sclerosis patients

et al. 2020

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“…18 Smartphone apps are being developed to evaluate skin and sclera coloration, aiming to make accurate jaundice predictions. One of these smartphone applications was developed by Padidar et al 19 to process pictures of the skin taken from the forehead of 113 newborns to analyze the RGB components of the images and a calibration card. When bilirubin levels were lower than 10 mg/dL, test sensitivity was 68% and specificity 92.3%; however, when bilirubin levels were lower than 15 mg/dL, sensitivity and specificity reached 82.1% and 100%, respectively.…”

Section: Jaundicementioning

confidence: 99%

Smartphone-based photo analysis for the evaluation of anemia, jaundice and COVID-19

Mazzu-Nascimento

Evangelista

Abubakar

et al. 2021

International Journal of Nutrology

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Anemia and jaundice are common health conditions that affect millions of children, adults, and the elderly worldwide. Recently, the pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), the virus that leads to COVID-19, has generated an extreme worldwide concern and a huge impact on public health, education, and economy, reaching all spheres of society. The development of techniques for non-invasive diagnosis and the use of mobile health (mHealth) is reaching more and more space. The analysis of a simple photograph by smartphone can allow an assessment of a person's health status. Image analysis techniques have advanced a lot in a short time. Analyses that were previously done manually, can now be done automatically by methods involving artificial intelligence. The use of smartphones, combined with machine learning techniques for image analysis (preprocessing, extraction of characteristics, classification, or regression), capable of providing predictions with high sensitivity and specificity, seems to be a trend. We presented in this review some highlights of the evaluation of anemia, jaundice, and COVID-19 by photo analysis, emphasizing the importance of using the smartphone, machine learning algorithms, and applications that are emerging rapidly. Soon, this will certainly be a reality. Also, these innovative methods will encourage the incorporation of mHealth technologies in telemedicine and the expansion of people's access to health services and early diagnosis.

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“…Research interest in smartphone-based jaundice screening is growing, and recent work is promising [15][16][17][18][19][20][21][22]. The most extensively validated system is the BiliCam app that estimates total serum bilirubin (TSB) based on the skin colour of the sternum [15].…”

Section: Plos Onementioning

confidence: 99%

Smartphone screening for neonatal jaundice via ambient-subtracted sclera chromaticity

et al. 2020

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Jaundice is a major cause of mortality and morbidity in the newborn. Globally, early identification and home monitoring are significant challenges in reducing the incidence of jaundicerelated neurological damage. Smartphone cameras are promising as colour-based screening tools as they are low-cost, objective and ubiquitous. We propose a novel smartphone method to screen for neonatal jaundice by imaging the sclera. It does not rely on colour calibration cards or accessories, which may facilitate its adoption at scale and in less economically developed regions. Our approach is to explicitly address three confounding factors in relating colour to jaundice: (1) skin pigmentation, (2) ambient light, and (3) camera spectral response. (1) The variation in skin pigmentation is avoided by imaging the sclera. (2) With the smartphone screen acting as an illuminating flash, a flash/ no-flash image pair is captured using the front-facing camera. The contribution of ambient light is subtracted. (3) In principle, this permits a device-and ambient-independent measure of sclera chromaticity following a one-time calibration. We introduce the concept of Scleral-Conjunctival Bilirubin (SCB), in analogy with Transcutaneous Bilirubin (TcB). The scleral chromaticity is mapped to an SCB value. A pilot study was conducted in the UCL Hospital Neonatal Care Unit (n = 37). Neonates were imaged using a specially developed app concurrently with having a blood test for total serum bilirubin (TSB). The better of two models for SCB based on ambient-subtracted sclera chromaticity achieved r = 0.75 (p<0.01) correlation with TSB. Ambient subtraction improved chromaticity estimates in proof-of-principle laboratory tests and screening performance within our study sample. Using an SCB decision threshold of 190μmol/L, the sensitivity was 100% (specificity 61%) in identifying newborns with TSB>250μmol/L (area under receiver operating characteristic curve, AUROC, 0.86), and 92% (specificity 67%) in identifying newborns with TSB>205μmol/L (AUROC 0.85). These results are comparable to modern transcutaneous bilirubinometers.

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Detection of Neonatal Jaundice by Using an Android OS-Based Smartphone Application

Cited by 29 publications

References 13 publications

The impact of social media use on depression in multiple sclerosis patients

The impact of social media use on depression in multiple sclerosis patients

Smartphone-based photo analysis for the evaluation of anemia, jaundice and COVID-19

Smartphone screening for neonatal jaundice via ambient-subtracted sclera chromaticity

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