ArticlePloS one2020
Smartphone screening for neonatal jaundice via ambient-subtracted sclera chromaticity.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06963450 (Clinical Investigation of the Smartphone App neoSCB to Perform Neonatal Jaundice Screening in Newborn Babies), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Clinical Investigation of the Smartphone App neoSCB to Perform Neonatal Jaundice Screening in Newborn Babies
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- Performance of smartphone application to accurately quantify hyperbilirubinemia in neonates: a systematic review with meta-analysis.European journal of pediatrics · 2023Pooled it
- Effects of a Smartphone-Based Out-of-Hospital Screening App for Neonatal Hyperbilirubinemia on Neonatal Readmission Rates and Maternal Anxiety: Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- [Expert consensus on artificial intelligence-assisted monitoring and management of neonatal jaundice in primary medical institutions (2026)].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Article
- Neonatal jaundice detection using a vision transformer-based deep learning model.Scientific reports · 2026Article
- Comparative Analysis of Classification of Neonatal Bilirubin by Using Various Machine Learning Approaches.Cureus · 2024Article
- Assessment of bilirubin levels in patients with cirrhosis via forehead, sclera and lower eyelid smartphone images.PLOS digital health · 2023Article
- The need for neonatal jaundice screening awareness in the Pakistani population: short communication.Annals of medicine and surgery (2012) · 2023Article
- Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study.Diagnostics (Basel, Switzerland) · 2023Article
- A novel smartphone scleral-image based tool for assessing jaundice in decompensated cirrhosis patients.Journal of gastroenterology and hepatology · 2023Article
- Feasibility of smartphone colorimetry of the face as an anaemia screening tool for infants and young children in Ghana.PloS one · 2023Article
- Demystifying non-invasive approaches for screening jaundice in low resource settings: a review.Frontiers in pediatrics · 2023Review
- Telemedicine as progressive treatment approach for neonatal jaundice due to the coronavirus disease 2019 pandemic.Clinical and experimental pediatrics · 2022Article
- On AI Approaches for Promoting Maternal and Neonatal Health in Low Resource Settings: A Review.Frontiers in public health · 2022Review
- Neonatal Jaundice Diagnosis Using a Smartphone Camera Based on Eye, Skin, and Fused Features with Transfer Learning.Sensors (Basel, Switzerland) · 2021Article
- Screening methods for neonatal hyperbilirubinemia: benefits, limitations, requirements, and novel developments.Pediatric research · 2021Review
- Smartphone-based imaging systems for medical applications: a critical review.Journal of biomedical optics · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
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 jaundice-related 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.