Evaluating the Viability of a Smartphone-Based Annotation Tool for Faster and Accurate Image Labelling for Artificial Intelligence in Diabetic Retinopathy

INTRODUCTION: Deep Learning (DL) and Artificial Intelligence (AI) have become widespread due to the advanced technologies and availability of digital data. Supervised learning algorithms have shown human-level performance or even better and are better feature extractor-quantifier than unsupervised l...

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Detalles Bibliográficos
Autores principales: Morya, Arvind Kumar, Gowdar, Jaitra, Kaushal, Abhishek, Makwana, Nachiket, Biswas, Saurav, Raj, Puneeth, Singh, Shabnam, Hegde, Sharat, Vaishnav, Raksha, Shetty, Sharan, S P, Vidyambika, Shah, Vedang, Paul, Sabita, Muralidhar, Sonali, Velis, Girish, Padua, Winston, Waghule, Tushar, Nazm, Nazneen, Jeganathan, Sangeetha, Reddy Mallidi, Ayyappa, Susan John, Dona, Sen, Sagnik, Choudhary, Sandeep, Parashar, Nishant, Sharma, Bhavana, Raghav, Pankaja, Udawat, Raghuveer, Ram, Sampat, Salodia, Umang P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953891/
https://www.ncbi.nlm.nih.gov/pubmed/33727785
http://dx.doi.org/10.2147/OPTH.S289425

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953891/
https://www.ncbi.nlm.nih.gov/pubmed/33727785
http://dx.doi.org/10.2147/OPTH.S289425

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