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References (24)

[1]
Artificial superintelligence alignment in healthcare.
2025Daiju Ueda, Shannon L. Walston et al.
[2]
Sequential Diagnosis with Language Models
2025Harsha Nori, M. Daswani et al.
[3]
A framework for evaluation and requirement extraction for fine-tuning of Large Language Models in multimodal medical diagnosis
2025D. Panagoulias, Anastasios Palamidas et al.
[4]
COGNET-MD, an evaluation framework and dataset for Large Language Model benchmarks in the medical domain
2024D. Panagoulias, Persephone Papatheodosiou et al.
[5]
Dermacen Analytica: A Novel Methodology Integrating Multi-Modal Large Language Models with Machine Learning in tele-dermatology
2024D. Panagoulias, Evridiki Tsoureli-Nikita et al.
[6]
Evaluating the Potential of LLMs and ChatGPT on Medical Diagnosis and Treatment
2023D. Panagoulias, Filippos A. Palamidas et al.
[7]
AI in health: keeping the human in the loop
2023S. Bakken
[8]
Large language models encode clinical knowledge
2022K. Singhal, Shekoofeh Azizi et al.
[9]
Human-in-the-loop machine learning: a state of the art
2022E. Mosqueira-Rey, Elena Hernández-Pereira et al.
[10]
Training language models to follow instructions with human feedback
2022Long Ouyang, Jeff Wu et al.
[11]
TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
2021Jieneng Chen, Yongyi Lu et al.
[12]
Training data-efficient image transformers & distillation through attention
2020Hugo Touvron, M. Cord et al.
[13]
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
2020Alexey Dosovitskiy, Lucas Beyer et al.
[14]
What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
2020Di Jin, Eileen Pan et al.
[15]
An overview of clinical decision support systems: benefits, risks, and strategies for success
2020Reed Taylor Sutton, D. Pincock et al.
[16]
PubMedQA: A Dataset for Biomedical Research Question Answering
2019Qiao Jin, Bhuwan Dhingra et al.
[17]
Studies on Different CNN Algorithms for Face Skin Disease Classification Based on Clinical Images
2019Zhe Wu, Shuang Zhao et al.
[18]
The importance of interpretability and visualization in machine learning for applications in medicine and health care
2019A. Vellido
[19]
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2018C. Rudin
[20]
Deep Reinforcement Learning from Human Preferences
2017P. Christiano, Jan Leike et al.

Showing 20 of 24 references

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