Every reference with a DOI in the deposited reference list resolved to a known
work in Crossref or DataCite at the dated check, and none carried a retraction,
withdrawal, or removal notice.
The 45 checked references that resolve
resolves10.1001/jama.2017.14585Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
resolves10.1093/jnci/djy225An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening
resolves10.1038/s41377-019-0129-yPhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning
resolves10.1038/s41551-019-0362-yVirtual histological staining of unlabelled tissue-autofluorescence images via deep learning
resolves10.1039/b705672aSample preparation: a challenge in the development of point-of-care nucleic acid-based assays for resource-limited settings
resolves10.1093/infdis/jis044Opportunities and Challenges for Cost-Efficient Implementation of New Point-of-Care Diagnostics for HIV and Tuberculosis
resolves10.1128/JCM.00476-17Point-of-Care Testing for Infectious Diseases: Past, Present, and Future
resolves10.1039/C6LC00737FPaper-based sensors and assays: a success of the engineering design and the convergence of knowledge areas
resolves10.1021/ac9013989Diagnostics for the Developing World: Microfluidic Paper-Based Analytical Devices
resolves10.1016/j.bios.2017.05.001Paper based diagnostics for personalized health care: Emerging technologies and commercial aspects
resolves10.1039/C8RA06132GThe potential of paper-based diagnostics to meet the ASSURED criteria
resolves10.1016/j.jim.2009.06.003The fundamental flaws of immunoassays and potential solutions using tandem mass spectrometry
resolves10.7150/thno.24034A hook effect-free immunochromatographic assay (HEF-ICA) for measuring the C-reactive protein concentration in one drop of human serum
resolves10.1016/j.bios.2014.04.032A three-line lateral flow assay strip for the measurement of C-reactive protein covering a broad physiological concentration range in human sera
resolves10.1021/acsnano.5b03203Cellphone-Based Hand-Held Microplate Reader for Point-of-Care Testing of Enzyme-Linked Immunosorbent Assays
resolves10.1021/acsnano.7b00105Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning
resolves10.1039/C4LC00010BMobile phones democratize and cultivate next-generation imaging, diagnostics and measurement tools
resolves10.1021/acsnano.9b08151Point-of-Care Serodiagnostic Test for Early-Stage Lyme Disease Using a Multiplexed Paper-Based Immunoassay and Machine Learning
resolves10.1039/C9AN00964GAlgorithms for immunochromatographic assay: review and impact on future application
resolves10.1007/s40820-019-0239-3Machine Learning Approach to Enhance the Performance of MNP-Labeled Lateral Flow Immunoassay
resolves10.1161/01.CIR.99.2.237C-Reactive Protein, a Sensitive Marker of Inflammation, Predicts Future Risk of Coronary Heart Disease in Initially Healthy Middle-Aged Men
resolves10.3390/s17040684Rapid and Low-Cost CRP Measurement by Integrating a Paper-Based Microfluidic Immunoassay with Smartphone (CRP-Chip)
resolves10.1016/j.aca.2017.12.031Quantitative and rapid detection of C-reactive protein using quantum dot-based lateral flow test strip
resolves10.1016/j.ab.2018.06.017Development of a lateral flow immunoassay of C-reactive protein detection based on red fluorescent nanoparticles
resolves10.1039/C9LC00011APaper-based multiplexed vertical flow assay for point-of-care testing
resolves10.1101/667436Deep Learning-Enabled Point-of-Care Sensing Using Multiplexed Paper-Based Sensors
The 6 references without a DOI — listed, not checked
no DOI — not checkedRivenson, Y. et al. Deep learning microscopy. Opt., Opt. 4, 1437–1443 (2017).
no DOI — not checkedPaper Diagnostics Market Worth $10.50 Billion by 2025 | CAGR: 8.0%. https://www.grandviewresearch.com/press-release/global-paper-diagnostics-market.
no DOI — not checked2013 ACC/AHA Guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults. Circulation https://www.ahajournals.org/doi/abs/10.1161/01.cir.0000437738.63853.7a (2014).
no DOI — not checkedHealth, C. for D. and R. Guidance Documents (Medical Devices and Radiation-Emitting Products)—Review Criteria for Assessment of C Reactive Protein (CRP), High Sensitivity C-Reactive Protein (hsCRP) and Cardiac C-Reactive Protein (cCRP) Assays—Guidance for Industry and FDA Staff. https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm077167.htm.
no DOI — not checkedBaldi, P. & Sadowski, P. J. Understanding Dropout. in Advances in Neural Information Processing Systems 26 (eds. Burges, C. J. C. et al.) 2814–2822 (Curran Associates, Inc., 2013).
no DOI — not checkedSrivastava, N. et al. Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929–1958 (2014).
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