Kusunose K, Okushi Y, Okayama Y, Zheng R, Nakai M, Sumita Y, Ise T, Yamaguchi K, Yagi S, Fukuda D, Yamada H, Soeki T, Wakatsuki T, Sata M. Use of echocardiography and heart failure in-hospital mortality from registry data in Japan. J Cardiovasc Dev Dis. 2021;8:124.

Article  PubMed  PubMed Central  Google Scholar 

Alsharqi M, Woodward W, Mumith J, Markham D, Upton R, Leeson P. Artificial intelligence and echocardiography. Echo Res Pract. 2018;5:R115–25.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sistrom CL, Langlotz CP. A framework for improving radiology reporting. J Am Coll Radiol. 2005;2:159–67.

Article  PubMed  Google Scholar 

Bell SK, Delbanco T, Elmore JG, Fitzgerald PS, Fossa A, Harcourt K, Leveille SG, Payne TH, Stametz RA, Walker J, DesRoches CM. Frequency and types of patient-reported errors in electronic health record ambulatory care notes. JAMA Netw Open. 2020;3: e205867.

Article  PubMed  PubMed Central  Google Scholar 

Mbakwe AB, Lourentzou I, Celi LA, Mechanic OJ, Dagan A. ChatGPT passing USMLE shines a spotlight on the flaws of medical education. PLOS Digit Health. 2023;2: e0000205.

Article  PubMed  PubMed Central  Google Scholar 

Kasai J, Kasai Y, Sakaguchi K, Yamada Y, Radev D (2023) Evaluating gpt-4 and chatgpt on japanese medical licensing examinations. arXiv preprint arXiv:230318027 2023

Sarraju A, Bruemmer D, Van Iterson E, Cho L, Rodriguez F, Laffin L. Appropriateness of cardiovascular disease prevention recommendations obtained from a popular online chat-based artificial intelligence model. JAMA. 2023;329:842–4.

Article  PubMed  Google Scholar 

Kusunose K, Kashima S, Sata M. Evaluation of the accuracy of ChatGPT in answering clinical questions on the Japanese Society of Hypertension Guidelines. Circ J 2023;87:1030–3.

Google Scholar 

Khan RA, Jawaid M, Khan AR, Sajjad M. ChatGPT-Reshaping medical education and clinical management. Pak J Med Sci. 2023;39:605.

Article  PubMed  PubMed Central  Google Scholar 

Kusunose K. Radiomics in echocardiography: deep learning and echocardiographic analysis. Curr Cardiol Rep. 2020;22:89.

Article  PubMed  Google Scholar 

Kusunose K, Abe T, Haga A, Fukuda D, Yamada H, Harada M, Sata M. A deep learning approach for assessment of regional wall motion abnormality from echocardiographic images. JACC Cardiovasc Imaging. 2020;13:374–81.

Article  PubMed  Google Scholar 

Kusunose K, Haga A, Inoue M, Fukuda D, Yamada H, Sata M. Clinically feasible and accurate view classification of echocardiographic images using deep learning. Biomolecules. 2020;10:665.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kusunose K, Haga A, Yamaguchi N, Abe T, Fukuda D, Yamada H, Harada M, Sata M. Deep learning for assessment of left ventricular ejection fraction from echocardiographic images. J Am Soc Echocardiogr. 2020;33(632–635): e631.

Google Scholar 

Morita SX, Kusunose K, Haga A, Sata M, Hasegawa K, Raita Y, Reilly MP, Fifer MA, Maurer MS, Shimada YJ. Deep learning analysis of echocardiographic images to predict positive genotype in patients with hypertrophic cardiomyopathy. Front Cardiovasc Med. 2021;8: 669860.

Article  PubMed  PubMed Central  Google Scholar 

Johnson KB, Wei WQ, Weeraratne D, Frisse ME, Misulis K, Rhee K, Zhao J, Snowdon JL. Precision medicine, AI, and the future of personalized health care. Clin Transl Sci. 2021;14:86–93.

Article  PubMed  Google Scholar 

Rajpurkar P, Chen E, Banerjee O, Topol EJ. AI in health and medicine. Nat Med. 2022;28:31–8.

Article  CAS  PubMed  Google Scholar 

Kusunose K. Steps to use artificial intelligence in echocardiography. J Echocardiogr. 2021;19:21–7.

Article  PubMed  Google Scholar 

Ghorbani A, Ouyang D, Abid A, He B, Chen JH, Harrington RA, Liang DH, Ashley EA, Zou JY. Deep learning interpretation of echocardiograms. NPJ Digit Med. 2020;3:10.

Article  PubMed  PubMed Central  Google Scholar 

Nagarhalli TP, Mhatre S, Patil S, Patil P. The review of natural language processing applications with emphasis on machine learning implementations 2022. In: International Conference on Electronics and Renewable Systems (ICEARS): IEEE, 2022; pp. 1353–1358.

Mitchell C, Rahko PS, Blauwet LA, Canaday B, Finstuen JA, Foster MC, Horton K, Ogunyankin KO, Palma RA, Velazquez EJ. Guidelines for performing a comprehensive transthoracic echocardiographic examination in adults: recommendations from the american society of echocardiography. J Am Soc Echocardiogr. 2019;32:1–64.

Article  PubMed  Google Scholar 

Otto CM. Practice of clinical echocardiography e-book. Elsevier Health Sciences; 2012.

Google Scholar 

Stoean C, Stoean R, Hotoleanu M, Iliescu D, Patru C, Nagy R. An assessment of the usefulness of image pre-processing for the classification of first trimester fetal heart ultrasound using convolutional neural networks 2021. In: 25th International Conference on System Theory, Control and Computing (ICSTCC): IEEE, 2021; pp. 242–248.

Kusunose K, Haga A, Inoue M, Fukuda D, Yamada H, Sata M. Clinically feasible and accurate view classification of echocardiographic images using deep learning. Biomolecules. 2020;10:665.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Teng L, Fu Z, Yao Y. Interactive translation in echocardiography training system with enhanced cycle-GAN. IEEE access. 2020;8:106147–56.

Article  Google Scholar 

Lecler A, Duron L, Soyer P. Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT. Diagn Interv Imaging. 2023;104:269–74.

Article  PubMed  Google Scholar 

Adams LC, Truhn D, Busch F, Kader A, Niehues SM, Makowski MR, Bressem KK. Leveraging GPT-4 for post hoc transformation of free-text radiology reports into structured reporting: a multilingual feasibility study. Radiology. 2023;307:230725.

Article  Google Scholar 

Parikh JR, Van Moore A, Mead L, Bassett R, Rubin E. Prevalence of burnout of radiologists in private practice. J Am Coll Radiol. 2023 Mar:S1546-1440(23)00196-5. https://doi.org/10.1016/j.jacr.2023.01.007

Willemink MJ, Koszek WA, Hardell C, Wu J, Fleischmann D, Harvey H, Folio LR, Summers RM, Rubin DL, Lungren MP. Preparing medical imaging data for machine learning. Radiology. 2020;295:4–15.

Article  PubMed  Google Scholar 

Brady AP, Neri E. Artificial intelligence in radiology—ethical considerations. Diagnostics. 2020;10:231.

Article  PubMed  PubMed Central  Google Scholar 

Group CAoRAIW. artificial intelligence in radiology. Can Assoc Radiolog J. 2019;70:107–18.

Google Scholar 

Panch T, Mattie H, Celi LA. The “inconvenient truth” about AI in healthcare. NPJ Digit Med. 2019;2:77.

Article  PubMed  PubMed Central  Google Scholar