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Kent Ryan Kleinschmidt on Muck Rack

Kent Ryan Kleinschmidt

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Articles

Repurposing adult AI radiograph models for neonatal care through continual learning: an international multicentre study

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By Vishwanatha M. Rao, Emma Chen, Agustina Saenz, Oishi Banerjee, sung kim, Evan H. Zucker, Susan C. Shelmerdine, Jeremy Palacio, Sathvik Suryadevara, Jiaxi Lu, Mario Scala, Julian F. Niedermair, Nikolaus Stranger, Sebastian Tschauner, Georg M. Schmölzer, Saif Afat, Thomas Küstner, Soroosh Tayebi Arasteh, Daniel Truhn, Kelsey L. Pomykala, Jens Kleesiek, Naela Himayati Afifah, Reza Shahriarirad, Amirhossein Erfani, Moria Be’er, Daiju Ueda, Alain S. Abi-Ghanem, Rafeah Khan, Zafar Iqbal, Amna A. Kashgari, Tijana Prodanovic, Nikola Prodanovic, Phumza Nongena, Melissa Cooke, Almudena Alonso-Ojembarrena, Alexandra Floriana Nemes, Yung-Chieh Lin, Wei-Ting Lin, Wen-Hui Fang, Chin Lin, Sira Sriswasdi, Didem Arman, Serdar Alan, Umit Ayse Tandircioglu, Esther Chung, Michael Sadler, Morgan P. McBee, Richard Jones, Pranav Rajpurkar, Henrik Marklund, Lucas Bijnens, Kent Ryan Kleinschmidt, Rithvik Akula, Oscar Jaramillo Robledo, Rozan M. Irfan, Yasuhito Mitsuyama, Safaa Al Zakleet, Naila Nizami, Khalid Al-Kharazi, Abdullah Al Shahrani, Montserrat Bret-Zurita, Atchara Mahayosnond, Piyapong Khumrin, Suphakris Tanmuk, Serdar Cömert, David Andrew Mong
| Nature Verified
Abstract Despite growing clinical adoption of artificial intelligence in radiology, fewer than one in five commercially available models are cleared for paediatric use. Existing systems are trained predominantly on adult data and generalize poorly to neonates, yet efficient strategies for repurposing them without data sharing or large-scale local data curation are lacking.
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