Výsledky vyhledávání - "ERYILMAZ, MERVE"

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Virtual Gram staining of label-free bacteria using darkfield microscopy and deep learning

Autor: Isil, Cagatay, Koydemir, Hatice Ceylan, Eryilmaz, Merve, de Haan, Kevin, Pillar, Nir, Mentesoglu, Koray, Unal, Aras Firat, Rivenson, Yair, Chandrasekaran, Sukantha, Garner, Omai B., Ozcan, Aydogan

Gram staining has been one of the most frequently used staining protocols in microbiology for over a century, utilized across various fields, including diagnostics, food safety, and environmental monitoring. Its manual procedures make it vulnerable t

Externí odkaz: http://arxiv.org/abs/2407.12337

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A paper-based multiplexed serological test to monitor immunity against SARS-CoV-2 using machine learning

Autor: Eryilmaz, Merve, Goncharov, Artem, Han, Gyeo-Re, Joung, Hyou-Arm, Ballard, Zachary S., Ghosh, Rajesh, Zhang, Yijie, Di Carlo, Dino, Ozcan, Aydogan

Publikováno v: ACS Nano (2024)

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest

Externí odkaz: http://arxiv.org/abs/2402.17774

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Deep learning-enhanced paper-based vertical flow assay for high-sensitivity troponin detection using nanoparticle amplification

Autor: Han, Gyeo-Re, Goncharov, Artem, Eryilmaz, Merve, Joung, Hyou-Arm, Ghosh, Rajesh, Yim, Geon, Chang, Nicole, Kim, Minsoo, Ngo, Kevin, Veszpremi, Marcell, Liao, Kun, Garner, Omai B., Di Carlo, Dino, Ozcan, Aydogan

Publikováno v: ACS Nano (2024)

Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, and data processing, couple

Externí odkaz: http://arxiv.org/abs/2402.11195

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Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning

Autor: Liu, Tairan, Li, Yuzhu, Koydemir, Hatice Ceylan, Zhang, Yijie, Yang, Ethan, Eryilmaz, Merve, Wang, Hongda, Li, Jingxi, Bai, Bijie, Ma, Guangdong, Ozcan, Aydogan

Publikováno v: Nature Biomedical Engineering (2023)

We present a rapid and stain-free quantitative viral plaque assay using lensfree holographic imaging and deep learning. This cost-effective, compact, and automated device significantly reduces the incubation time needed for traditional plaque assays

Externí odkaz: http://arxiv.org/abs/2207.00089

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