Research map: Bayesian models to forecast complications and their severity in type 2 diabetes

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Papers in this map

  1. SMOTE: Synthetic Minority Over-sampling Technique · Nitesh V. Chawla · 2002 · 32823 citations · Cited by this paper
  2. Enhancing discharge location prediction for patients undergoing orthopedic surgery using side-tuning · 2026 · Related
  3. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021 · Kanyin Liane Ong · 2023 · 4687 citations · Cited by this paper
  4. KAMDA: A multi-view Kolmogorov-Arnold Network integrating pre-trained BERT embeddings and similarity-based imputation for microbe-drug association prediction · 2026 · Related
  5. Machine Learning Methods to Predict Diabetes Complications · Arianna Dagliati · 2017 · 436 citations · Cited by this paper
  6. Multi-dataset lung and colon cancer histopathology classification using hybrid CNN-vision transformer · 2026 · Related
  7. Bayesian Networks for Risk Prediction Using Real-World Data: A Tool for Precision Medicine · Paul Arora · 2019 · 201 citations · Cited by this paper
  8. Efficient Few-Shot Learning for Medical Image Classification: A Practical Review of Lightweight and Resource-Aware Approaches · 2026 · Related
  9. Bayesian networks for interpretable machine learning and optimization · Bojan Mihaljević · 2021 · 119 citations · Cited by this paper
  10. LiT-HiSegFormer-Net: A hybrid SegFormer network with Bi-level context fusion for liver and tumor segmentation in CT images · 2026 · Related
  11. Artificial Intelligence Applications in Type 2 Diabetes Mellitus Care: Focus on Machine Learning Methods · Shahabeddin Abhari · 2019 · 104 citations · Cited by this paper
  12. Compact attention-driven deep network for interpretable oral squamous cell carcinoma screening · 2026 · Related
  13. Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach · Ali Aminian · 2020 · 100 citations · Cited by this paper
  14. HyFormer-Net: A synergistic CNN-Transformer with interpretable multi-scale fusion for breast lesion segmentation and classification in ultrasound images · 2026 · Related
  15. Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study · Ariana Anderson · 2015 · 99 citations · Cited by this paper
  16. Validation of webcam-based eye-tracking for clinically relevant paradigms: Saccade, attention bias, and free-viewing tasks · 2026 · Related
  17. Prediction of complications of type 2 Diabetes: A Machine learning approach · Antonio Nicolucci · 2022 · 65 citations · Cited by this paper
  18. Applications of artificial intelligence in rare skin diseases and skin cancers: A scoping review · 2026 · Related
  19. Nationwide prediction of type 2 diabetes comorbidities · Piotr Dworzyński · 2020 · 58 citations · Cited by this paper
  20. Leveraging retinal vessel segmentation for improved disease classification · 2026 · Related
  21. Prediction of Incident Diabetes in the Jackson Heart Study Using High-Dimensional Machine Learning · Ramon Casanova · 2016 · 57 citations · Cited by this paper
  22. Predicting the onset of diabetes-related complications after a diabetes diagnosis with machine learning algorithms · Toni Mora · 2023 · 50 citations · Cited by this paper
  23. Advanced Techniques for Predicting the Future Progression of Type 2 Diabetes · Md Shafiqul Islam · 2020 · 39 citations · Cited by this paper
  24. Complication Risk Profiling in Diabetes Care: A Bayesian Multi-Task and Feature Relationship Learning Approach · Bin Liu · 2019 · 35 citations · Cited by this paper
  25. Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model development and validation study · Hayeon Lee · 2025 · 30 citations · Cited by this paper
  26. Predicting onset of complications from diabetes: a graph based approach · Pamela Bilo Thomas · 2018 · 24 citations · Cited by this paper
  27. Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities · Danli Kong · 2024 · 24 citations · Cited by this paper
  28. Predictive models of diabetes complications: protocol for a scoping review · Ruth Ndjaboué · 2020 · 21 citations · Cited by this paper
  29. Performance evaluation of diabetes with machine learning algorithms · Salliah Shafi Bhat · 2024 · 7 citations · Cited by this paper
  30. Predictive analysis for diabetes mellitus prediction using supervised techniques · Salliah Shafi Bhat · 2024 · 6 citations · Cited by this paper
  31. Enhancing diabetes complications prediction through knowledge graphs and convolutional networks · Haitao Cheng · 2025 · 6 citations · Cited by this paper
  32. Understanding Bayesian analysis of clinical trials: an overview for clinicians · Callum Taylor · 2025 · 3 citations · Cited by this paper
  33. A machine learning algorithm for the prediction of complications incorporated in electronic medical records improves type 2 diabetes care · Antonio Nicolucci · 2025 · 2 citations · Cited by this paper

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