
@article{zeleznik2021deep,
  title={Deep convolutional neural networks to predict cardiovascular risk from computed tomography},
  author={Zeleznik, Roman and Foldyna, Borek and Eslami, Parastou and Weiss, Jakob and Alexander, Ivanov and Taron, Jana and Parmar, Chintan and Alvi, Raza M and Banerji, Dahlia and Uno, Mio and others},
  journal={Nature communications},
  volume={12},
  number={1},
  pages={715},
  year={2021},
  publisher={Nature Publishing Group UK London}
}

@article{pickhardt2020automated,
  title={Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study},
  author={Pickhardt, Perry J and Graffy, Peter M and Zea, Ryan and Lee, Scott J and Liu, Jiamin and Sandfort, Veit and Summers, Ronald M},
  journal={The Lancet Digital Health},
  volume={2},
  number={4},
  pages={e192--e200},
  year={2020},
  publisher={Elsevier}
}
@inproceedings{huang2025opportunistic,
  title={Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration},
  author={Huang, Jiaxing and Guo, Heng and Lu, Le and Yang, Fan and Xu, Minfeng and Yang, Ge and Luo, Wei},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={428--438},
  year={2025},
  organization={Springer}
}
@inproceedings{ramanarayanan2020mac,
  title={Mac-reconnet: A multiple acquisition context based convolutional neural network for mr image reconstruction using dynamic weight prediction},
  author={Ramanarayanan, Sriprabha and Murugesan, Balamurali and Ram, Keerthi and Sivaprakasam, Mohanasankar},
  booktitle={Medical Imaging with Deep Learning},
  pages={696--708},
  year={2020},
  organization={PMLR}
}
@article{li2025deep,
  title={Deep Learning-enhanced Opportunistic Osteoporosis Screening in Ultralow-Voltage (80 kV) Chest CT: A Preliminary Study},
  author={Li, Yali and Liu, Suwei and Zhang, Yan and Zhang, Mengze and Jiang, Chenyu and Ni, Ming and Jin, Dan and Qian, Zhen and Wang, Jiangxuan and Pan, Xuemin and others},
  journal={Academic Radiology},
  year={2025},
  publisher={Elsevier}
}
@article{lenchik2018opportunistic,
  title={Opportunistic screening for osteoporosis using computed tomography: state of the art and argument for paradigm shift},
  author={Lenchik, Leon and Weaver, Ashley A and Ward, Robert J and Boone, John M and Boutin, Robert D},
  journal={Current rheumatology reports},
  volume={20},
  number={12},
  pages={74},
  year={2018},
  publisher={Springer}
}
@article{foraker2025opportunistic,
  title={Opportunistic Detection of Coronary Artery Calcium on Noncardiac Chest Computed Tomography: An Emerging Tool for Cardiovascular Disease Prevention: A Scientific Statement From the American Heart Association},
  author={Foraker, Randi and Sperling, Laurence and Bratzke, Lisa and Budoff, Matthew and Leppert, Michelle and Razavi, Alexander C and Rodriguez, Fatima and Shapiro, Michael D and Whelton, Seamus and Wong, Nathan D and others},
  journal={Circulation},
  volume={152},
  number={19},
  pages={e391--e401},
  year={2025},
  publisher={Lippincott Williams \& Wilkins Hagerstown, MD}
}
@article{pickhardt2023opportunistic,
  title={Opportunistic screening: radiology scientific expert panel},
  author={Pickhardt, Perry J and Summers, Ronald M and Garrett, John W and Krishnaraj, Arun and Agarwal, Sheela and Dreyer, Keith J and Nicola, Gregory N},
  journal={Radiology},
  volume={307},
  number={5},
  pages={e222044},
  year={2023},
  publisher={Radiological Society of North America}
}
@misc{rsna-pneumonia-detection-challenge,
    author = {Anouk Stein, MD and Carol Wu and Chris Carr and George Shih and Jamie Dulkowski and kalpathy and Leon Chen and Luciano Prevedello and Marc Kohli, MD and Mark McDonald and Peter and Phil Culliton and Safwan Halabi MD and Tian Xia},
    title = {RSNA Pneumonia Detection Challenge},
    year = {2018},
    howpublished = {\url{https://kaggle.com/competitions/rsna-pneumonia-detection-challenge}},
    note = {Kaggle}
}
@article{hamamci2024developing,
  title={Developing generalist foundation models from a multimodal dataset for 3d computed tomography},
  author={Hamamci, Ibrahim Ethem and Er, Sezgin and Wang, Chenyu and Almas, Furkan and Simsek, Ayse Gulnihan and Esirgun, Sevval Nil and Dogan, Irem and Durugol, Omer Faruk and Hou, Benjamin and Shit, Suprosanna and others},
  journal={arXiv preprint arXiv:2403.17834},
  year={2024}
}
@article{ha2016hypernetworks,
  title={Hypernetworks},
  author={Ha, David and Dai, Andrew and Le, Quoc V},
  journal={arXiv preprint arXiv:1609.09106},
  year={2016}
}
@article{navon2022multi,
  title={Multi-task learning as a bargaining game},
  author={Navon, Aviv and Shamsian, Aviv and Achituve, Idan and Maron, Haggai and Kawaguchi, Kenji and Chechik, Gal and Fetaya, Ethan},
  journal={arXiv preprint arXiv:2202.01017},
  year={2022}
}
@inproceedings{chen2018gradnorm,
  title={Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks},
  author={Chen, Zhao and Badrinarayanan, Vijay and Lee, Chen-Yu and Rabinovich, Andrew},
  booktitle={International conference on machine learning},
  pages={794--803},
  year={2018},
  organization={PMLR}
}
@article{yu2020gradient,
  title={Gradient surgery for multi-task learning},
  author={Yu, Tianhe and Kumar, Saurabh and Gupta, Abhishek and Levine, Sergey and Hausman, Karol and Finn, Chelsea},
  journal={Advances in neural information processing systems},
  volume={33},
  pages={5824--5836},
  year={2020}
}
@article{sener2018multi,
  title={Multi-task learning as multi-objective optimization},
  author={Sener, Ozan and Koltun, Vladlen},
  journal={Advances in neural information processing systems},
  volume={31},
  year={2018}
}
@inproceedings{liu2019end,
  title={End-to-end multi-task learning with attention},
  author={Liu, Shikun and Johns, Edward and Davison, Andrew J},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={1871--1880},
  year={2019}
}
@article{national2011reduced,
  title={Reduced lung-cancer mortality with low-dose computed tomographic screening},
  author={National Lung Screening Trial Research Team},
  journal={New England Journal of Medicine},
  volume={365},
  number={5},
  pages={395--409},
  year={2011},
  publisher={Mass Medical Soc}
}
@article{lee2025prostate,
  title={Prostate-specific foundation models for enhanced detection of clinically significant cancer},
  author={Lee, Jeong Hoon and Li, Cynthia Xinran and Jahanandish, Hassan and Bhattacharya, Indrani and Vesal, Sulaiman and Zhang, Lichun and Sang, Shengtian and Choi, Moon Hyung and Soerensen, Simon John Christoph and Zhou, Steve Ran and others},
  journal={arXiv preprint arXiv:2502.00366},
  year={2025}
}
@article{wang2024instantid,
  title={Instantid: Zero-shot identity-preserving generation in seconds},
  author={Wang, Qixun and Bai, Xu and Wang, Haofan and Qin, Zekui and Chen, Anthony and Li, Huaxia and Tang, Xu and Hu, Yao},
  journal={arXiv preprint arXiv:2401.07519},
  year={2024}
}
@article{hamamci2023generatect,
  title={Generatect: Text-conditional generation of 3d chest ct volumes},
  author={Hamamci, Ibrahim Ethem and Er, Sezgin and Sekuboyina, Anjany and Simsar, Enis and Tezcan, Alperen and Simsek, Ayse Gulnihan and Esirgun, Sevval Nil and Almas, Furkan and Dogan, Irem and Dasdelen, Muhammed Furkan and others},
  journal={arXiv preprint arXiv:2305.16037},
  year={2023}
}
@article{grattafiori2024llama,
  title={The llama 3 herd of models},
  author={Grattafiori, Aaron and Dubey, Abhimanyu and Jauhri, Abhinav and Pandey, Abhinav and Kadian, Abhishek and Al-Dahle, Ahmad and Letman, Aiesha and Mathur, Akhil and Schelten, Alan and Vaughan, Alex and others},
  journal={arXiv preprint arXiv:2407.21783},
  year={2024}
}
@article{navon2020learning,
  title={Learning the pareto front with hypernetworks},
  author={Navon, Aviv and Shamsian, Aviv and Chechik, Gal and Fetaya, Ethan},
  journal={arXiv preprint arXiv:2010.04104},
  year={2020}
}
@article{mahabadi2021parameter,
  title={Parameter-efficient multi-task fine-tuning for transformers via shared hypernetworks},
  author={Mahabadi, Rabeeh Karimi and Ruder, Sebastian and Dehghani, Mostafa and Henderson, James},
  journal={arXiv preprint arXiv:2106.04489},
  year={2021}
}

@misc{raikhelkar2025artificial,
  title={An Artificial Intelligence Model to Detect Abnormal Ejection Fraction from Non-Contrast Chest Computed Tomography: The CT-LVEF study},
  author={Raikhelkar, Jayant and Bai, Zilong and Beecy, Ashley and Liu, Fengbei and Nizam, Nusrat and Kishore, Varsha and Kelsey, Chris and Ruhl, Jeffrey and Tesfuzigta, Naomi and Lancet, Erica and others},
  note={Preprint},
  year={2025}
}
@inproceedings{yao2022effective,
  title={Effective opportunistic esophageal cancer screening using noncontrast CT imaging},
  author={Yao, Jiawen and Ye, Xianghua and Xia, Yingda and Zhou, Jian and Shi, Yu and Yan, Ke and Wang, Fang and Lin, Lili and Yu, Haogang and Hua, Xian-Sheng and others},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={344--354},
  year={2022},
  organization={Springer}
}
@article{li2023quantifying,
  title={Quantifying emphysema in lung screening computed tomography with robust automated lobe segmentation},
  author={Li, Thomas Z and Hin Lee, Ho and Xu, Kaiwen and Gao, Riqiang and Dawant, Benoit M and Maldonado, Fabien and Sandler, Kim L and Landman, Bennett A},
  journal={Journal of Medical Imaging},
  volume={10},
  number={4},
  pages={044002--044002},
  year={2023},
  publisher={Society of Photo-Optical Instrumentation Engineers}
}
@article{setio2017validation,
  title={Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge},
  author={Setio, Arnaud Arindra Adiyoso and Traverso, Alberto and De Bel, Thomas and Berens, Moira SN and Van Den Bogaard, Cas and Cerello, Piergiorgio and Chen, Hao and Dou, Qi and Fantacci, Maria Evelina and Geurts, Bram and others},
  journal={Medical image analysis},
  volume={42},
  pages={1--13},
  year={2017},
  publisher={Elsevier}
}

@article{humphries2020deep,
  title={Deep learning enables automatic classification of emphysema pattern at CT},
  author={Humphries, Stephen M and Notary, Aleena M and Centeno, Juan Pablo and Strand, Matthew J and Crapo, James D and Silverman, Edwin K and Lynch, David A and Genetic Epidemiology of COPD (COPDGene) Investigators},
  journal={Radiology},
  volume={294},
  number={2},
  pages={434--444},
  year={2020},
  publisher={Radiological Society of North America}
}
@article{lin2021reasonable,
  title={Reasonable effectiveness of random weighting: A litmus test for multi-task learning},
  author={Lin, Baijiong and Ye, Feiyang and Zhang, Yu and Tsang, Ivor W},
  journal={arXiv preprint arXiv:2111.10603},
  year={2021}
}
@inproceedings{kendall2018multi,
  title={Multi-task learning using uncertainty to weigh losses for scene geometry and semantics},
  author={Kendall, Alex and Gal, Yarin and Cipolla, Roberto},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={7482--7491},
  year={2018}
}
@article{lin2023libmtl,
  title={{LibMTL}: A {P}ython Library for Multi-Task Learning},
  author={Baijiong Lin and Yu Zhang},
  journal={Journal of Machine Learning Research},
  volume={24},
  number={209},
  pages={1--7},
  year={2023}
}

@article{loshchilov2017decoupled,
  title={Decoupled weight decay regularization},
  author={Loshchilov, Ilya and Hutter, Frank},
  journal={arXiv preprint arXiv:1711.05101},
  year={2017}
}
@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}

@article{simeoni2025dinov3,
  title={Dinov3},
  author={Sim{\'e}oni, Oriane and Vo, Huy V and Seitzer, Maximilian and Baldassarre, Federico and Oquab, Maxime and Jose, Cijo and Khalidov, Vasil and Szafraniec, Marc and Yi, Seungeun and Ramamonjisoa, Micha{\"e}l and others},
  journal={arXiv preprint arXiv:2508.10104},
  year={2025}
}

@article{paszke2019pytorch,
  title={Pytorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}
# MTL
@inproceedings{misra2016cross,
  title={Cross-stitch networks for multi-task learning},
  author={Misra, Ishan and Shrivastava, Abhinav and Gupta, Abhinav and Hebert, Martial},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={3994--4003},
  year={2016}
}

@inproceedings{ruder2019latent,
  title={Latent multi-task architecture learning},
  author={Ruder, Sebastian and Bingel, Joachim and Augenstein, Isabelle and S{\o}gaard, Anders},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={33},
  pages={4822--4829},
  year={2019}
}

@inproceedings{gao2020mtl,
  title={Mtl-nas: Task-agnostic neural architecture search towards general-purpose multi-task learning},
  author={Gao, Yuan and Bai, Haoping and Jie, Zequn and Ma, Jiayi and Jia, Kui and Liu, Wei},
  booktitle={Proceedings of the IEEE/CVF Conference on computer vision and pattern recognition},
  pages={11543--11552},
  year={2020}
}


@article{caruana1997multitask,
  title={Multitask learning},
  author={Caruana, Rich},
  journal={Machine learning},
  volume={28},
  number={1},
  pages={41--75},
  year={1997},
  publisher={Springer}
}

@inproceedings{guo2020learning,
  title={Learning to branch for multi-task learning},
  author={Guo, Pengsheng and Lee, Chen-Yu and Ulbricht, Daniel},
  booktitle={International conference on machine learning},
  pages={3854--3863},
  year={2020},
  organization={PMLR}
}

@inproceedings{chen2023mod,
  title={Mod-squad: Designing mixtures of experts as modular multi-task learners},
  author={Chen, Zitian and Shen, Yikang and Ding, Mingyu and Chen, Zhenfang and Zhao, Hengshuang and Learned-Miller, Erik G and Gan, Chuang},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={11828--11837},
  year={2023}
}

@inproceedings{mehta2018net,
  title={Y-Net: joint segmentation and classification for diagnosis of breast biopsy images},
  author={Mehta, Sachin and Mercan, Ezgi and Bartlett, Jamen and Weaver, Donald and Elmore, Joann G and Shapiro, Linda},
  booktitle={International conference on medical image computing and computer-assisted intervention},
  pages={893--901},
  year={2018},
  organization={Springer}
}

@article{niu2023specialty,
  title={Specialty-oriented generalist medical ai for chest ct screening},
  author={Niu, Chuang and Lyu, Qing and Carothers, Christopher D and Kaviani, Parisa and Tan, Josh and Yan, Pingkun and Kalra, Mannudeep K and Whitlow, Christopher T and Wang, Ge},
  journal={arXiv preprint arXiv:2304.02649},
  year={2023}
}

@article{zhou2021multi,
  title={Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images},
  author={Zhou, Yue and Chen, Houjin and Li, Yanfeng and Liu, Qin and Xu, Xuanang and Wang, Shu and Yap, Pew-Thian and Shen, Dinggang},
  journal={Medical image analysis},
  volume={70},
  pages={101918},
  year={2021},
  publisher={Elsevier}
}

@article{
lin2022reasonable,
title={Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning},
author={Baijiong Lin and Feiyang Ye and Yu Zhang and Ivor Tsang},
journal={Transactions on Machine Learning Research},
issn={2835-8856},
year={2022},
url={https://openreview.net/forum?id=jjtFD8A1Wx},
note={}
}



@inproceedings{chennupati2019multinet++,
  title={Multinet++: Multi-stream feature aggregation and geometric loss strategy for multi-task learning},
  author={Chennupati, Sumanth and Sistu, Ganesh and Yogamani, Senthil and A Rawashdeh, Samir},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops},
  pages={0--0},
  year={2019}
}



% parameter-efficient

@article{hu2022lora,
  title={Lora: Low-rank adaptation of large language models.},
  author={Hu, Edward J and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu and others},
  journal={ICLR},
  volume={1},
  number={2},
  pages={3},
  year={2022}
}

@inproceedings{liu2024dora,
  title={Dora: Weight-decomposed low-rank adaptation},
  author={Liu, Shih-Yang and Wang, Chien-Yi and Yin, Hongxu and Molchanov, Pavlo and Wang, Yu-Chiang Frank and Cheng, Kwang-Ting and Chen, Min-Hung},
  booktitle={Forty-first International Conference on Machine Learning},
  year={2024}
}

@article{dettmers2023qlora,
  title={Qlora: Efficient finetuning of quantized llms},
  author={Dettmers, Tim and Pagnoni, Artidoro and Holtzman, Ari and Zettlemoyer, Luke},
  journal={Advances in neural information processing systems},
  volume={36},
  pages={10088--10115},
  year={2023}
}

@article{zhong2024convolution,
  title={Convolution meets lora: Parameter efficient finetuning for segment anything model},
  author={Zhong, Zihan and Tang, Zhiqiang and He, Tong and Fang, Haoyang and Yuan, Chun},
  journal={arXiv preprint arXiv:2401.17868},
  year={2024}
}

@article{
zhong2024multilora,
title={Multi-Lo{RA} Composition for Image Generation},
author={Ming Zhong and yelong shen and Shuohang Wang and Yadong Lu and Yizhu Jiao and Siru Ouyang and Donghan Yu and Jiawei Han and Weizhu Chen},
journal={Transactions on Machine Learning Research},
issn={2835-8856},
year={2024},
url={https://openreview.net/forum?id=25FT0DqhVZ},
note={}
}

@article{chen2024sv,
  title={SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding},
  author={Chen, Jian and Zhang, Ruiyi and Zhou, Yufan and Yu, Tong and Dernoncourt, Franck and Gu, Jiuxiang and Rossi, Ryan A and Chen, Changyou and Sun, Tong},
  journal={arXiv preprint arXiv:2411.01106},
  year={2024}
}

@article{liu2023visual,
  title={Visual instruction tuning},
  author={Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
  journal={Advances in neural information processing systems},
  volume={36},
  pages={34892--34916},
  year={2023}
}

@inproceedings{ohs2019hypercl,
title={Continual learning with hypernetworks},
author={Johannes von Oswald and Christian Henning and Benjamin F. Grewe and Jo{\~a}o Sacramento},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://arxiv.org/abs/1906.00695}
}

@inproceedings{sendera2023hypershot,
  title={Hypershot: Few-shot learning by kernel hypernetworks},
  author={Sendera, Marcin and Przewi{k{e}}{\'z}likowski, Marcin and Karanowski, Konrad and Zi{k{e}}ba, Maciej and Tabor, Jacek and Spurek, Przemys{\l}aw},
  booktitle={Proceedings of the IEEE/CVF winter conference on applications of computer vision},
  pages={2469--2478},
  year={2023}
}

@inproceedings{dinh2022hyperinverter,
  title={Hyperinverter: Improving stylegan inversion via hypernetwork},
  author={Dinh, Tan M and Tran, Anh Tuan and Nguyen, Rang and Hua, Binh-Son},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={11389--11398},
  year={2022}
}

@inproceedings{ruiz2024hyperdreambooth,
  title={Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models},
  author={Ruiz, Nataniel and Li, Yuanzhen and Jampani, Varun and Wei, Wei and Hou, Tingbo and Pritch, Yael and Wadhwa, Neal and Rubinstein, Michael and Aberman, Kfir},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={6527--6536},
  year={2024}
}

@inproceedings{karimi2021parameterefficient,
  title={Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks},
  author={Karimi Mahabadi, Rabeeh and Ruder, Sebastian and Dehghani, Mostafa and Henderson, James},
  booktitle={Annual Meeting of the Association for Computational Linguistics},
  year={2021}
}

@article{duenias2025hyperfusion,
  title={Hyperfusion: A hypernetwork approach to multimodal integration of tabular and medical imaging data for predictive modeling},
  author={Duenias, Daniel and Nichyporuk, Brennan and Arbel, Tal and Raviv, Tammy Riklin and others},
  journal={Medical Image Analysis},
  volume={102},
  pages={103503},
  year={2025},
  publisher={Elsevier}
}

@inproceedings{serebro2025hyda,
  title={HyDA: Hypernetworks for Test Time Domain Adaptation in Medical Imaging Analysis},
  author={Serebro, Doron and Riklin-Raviv, Tammy},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={251--261},
  year={2025},
  organization={Springer}
}

@article{hong2021hypernet,
  title={Hypernet-ensemble learning of segmentation probability for medical image segmentation with ambiguous labels},
  author={Hong, Sungmin and Bonkhoff, Anna K and Hoopes, Andrew and Bretzner, Martin and Schirmer, Markus D and Giese, Anne-Katrin and Dalca, Adrian V and Golland, Polina and Rost, Natalia S},
  journal={arXiv preprint arXiv:2112.06693},
  year={2021}
}


% misc
@inproceedings{gu2025vision,
  title={Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?},
  author={Gu, Hanxue and Chen, Yaqian and Konz, Nicholas and Li, Qihang and Mazurowski, Maciej A},
  booktitle={Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care},
  pages={101--112},
  year={2025},
  organization={Springer}
}

@article{dorfner2024performance,
  title={Performance of an Open-Source Large Language Model in Extracting Information from Free-Text Radiology Reports},
  author={Dorfner, Felix J and Juber, Amin and Guthier, Jens and Gupta, Saurav and Jain, Ritvik and Sethi, Pooja and others},
  journal={Radiology: Artificial Intelligence},
  volume={6},
  number={4},
  pages={e230364},
  year={2024},
  publisher={Radiological Society of North America}
}

@article{kheradmand2025automated,
  title={Automated Radiology Report Labeling in Chest X-Ray Pathologies: Development and Evaluation of a Large Language Model Framework},
  author={Kheradmand, Emad and Fathi, Saloua and Katzorke, Nils and Shafiei, Afshin},
  journal={JMIR Medical Informatics},
  volume={13},
  pages={e68618},
  year={2025},
  publisher={JMIR Publications}
}

@article{vickers2006decision,
  title={Decision Curve Analysis: A Novel Method for Evaluating Prediction Models},
  author={Vickers, Andrew J and Elkin, Elena B},
  journal={Medical Decision Making},
  volume={26},
  number={6},
  pages={565--574},
  year={2006},
  publisher={SAGE Publications}
}

@article{johnson1967hierarchical,
  title={Hierarchical clustering schemes},
  author={Johnson, Stephen C},
  journal={Psychometrika},
  volume={32},
  number={3},
  pages={241--254},
  year={1967},
  publisher={Springer}
}

@article{rousseeuw1987silhouettes,
  title={Silhouettes: a graphical aid to the interpretation and validation of cluster analysis},
  author={Rousseeuw, Peter J},
  journal={Journal of Computational and Applied Mathematics},
  volume={20},
  pages={53--65},
  year={1987},
  publisher={Elsevier}
}

@article{torgerson1952multidimensional,
  title={Multidimensional scaling: {I}. {T}heory and method},
  author={Torgerson, Warren S},
  journal={Psychometrika},
  volume={17},
  number={4},
  pages={401--419},
  year={1952},
  publisher={Springer}
}

@inproceedings{perez2018film,
  title={{FiLM}: Visual reasoning with a general conditioning layer},
  author={Perez, Ethan and Strub, Florian and De Vries, Harm and Dumoulin, Vincent and Courville, Aaron},
  booktitle={AAAI Conference on Artificial Intelligence},
  volume={32},
  year={2018}
}

@inproceedings{ramzi2020benchmarking,
  title={Benchmarking {MRI} reconstruction neural networks on large public datasets},
  author={Ramzi, Zaccharie and Ciuciu, Philippe and Starck, Jean-Luc},
  booktitle={Applied Sciences},
  volume={10},
  number={5},
  pages={1816},
  year={2020}
}

@article{zhao2020metainvnet,
  title={{MetaInv-Net}: Meta inversion network for sparse view {CT} image reconstruction},
  author={Zhao, Haimiao and Zhang, Jie and Wei, Bo and Jin, Guoqiang and Tian, Zhiqiang and Sun, Yi},
  journal={IEEE Transactions on Medical Imaging},
  volume={40},
  number={2},
  pages={621--634},
  year={2020},
  publisher={IEEE}
}

@inproceedings{hoopes2021hypermorph,
  title={{HyperMorph}: Amortized hyperparameter learning for image registration},
  author={Hoopes, Andrew and Hoffmann, Malte and Fischl, Bruce and Guttag, John and Dalca, Adrian V},
  booktitle={International Conference on Information Processing in Medical Imaging},
  pages={3--17},
  year={2021},
  organization={Springer}
}
