2025, Number 3
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Arch Med Fam 2025; 27 (3)
Model Personalization and Training with TensorFlow: Important Challenges for Modern Medicine
Hernández-Navas JA, Dulcey-Sarmiento L, Gómez- Ayala J, Therán-León JS
Language: Spanish
References: 7
Page: 103-104
PDF size: 130.32 Kb.
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REFERENCES
Akbari A, Martinez J, Jafari R. A Meta-LearningApproach for Fast Personalization of Modality TranslationModels in Wearable Physiological Sensing. IEEEJ Biomed Health Inform [Internet]. 2022 Apr 1 [cited 2025 Apr 1];26(4):1516–27. Available from: https://pubmed.ncbi.nlm.nih.gov/34398767/
Zhao Y, Liu Q, Liu P, Liu X, He K. Medical FederatedModel With Mixture of Personalized and Shared Components.IEEE Trans Pattern Anal Mach Intell. 2025Jan;47(1):433-449. doi: 10.1109/TPAMI.2024.3470072.Epub 2024 Dec 4. PMID: 39331555.
Raza M. Federated Learning in AI: How It Works, Benefitsand Challenges. Splunk. August 28, 2023. Availablefrom: https://www.splunk.com/en_us/blog/learn/federated-ai.html#:~:text=El%20aprendizaje%20federado%20en%20inteligencia,un%20sistema%20de%20entrenamiento%20unificado.
Ley 1581 de 2012 - Gestor Normativo [Internet]. Gov.co.[citado el 6 de junio de 2025]. Disponible en: https://www.funcionpublica.gov.co/eva/gestornormativo/norma.php?i=49981
Zeng X, Linwood SL, Liu C. Pretrained transformer frameworkon pediatric claims data for population specifictasks. Sci Rep [Internet]. 2022 Dec 1 [cited 2025 Apr1];12(1). Available from: https://pubmed.ncbi.nlm.nih.gov/35256645/
Ravishankar H, Paluru N, Sudhakar P, Yalavarthy PK.Information Geometric Approaches for Patient-SpecificTest-Time Adaptation of Deep Learning Modelsfor Semantic Segmentation. IEEE Trans Med Imaging[Internet]. 2025 [cited 2025 Apr 1];PP. Available from:https://pubmed.ncbi.nlm.nih.gov/40031589/
Zhang YC, Kagen AC. Machine Learning Interface forMedical Image Analysis. J Digit Imaging [Internet].2017 Oct 1 [cited 2025 Apr 1];30(5):615–21. Availablefrom: https://pubmed.ncbi.nlm.nih.gov/27730415/
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