Automatic Medical Report Generation via Latent Space Conditioning and Transformers
This paper presents a comprehensive exploration of integrating artificial intelligence (AI) in the healthcare sector, focusing on the development and implementation of a novel framework called VAE-GPT. Our architecture combines Variational Autoencoder (VAE) and Generative Pre-trained Transformer (GP...
Uloženo v:
| Vydáno v: | IEEE International Conference on Dependable, Autonomic and Secure Computing (Online) s. 0428 - 0435 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
14.11.2023
|
| Témata: | |
| ISSN: | 2837-0740 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | This paper presents a comprehensive exploration of integrating artificial intelligence (AI) in the healthcare sector, focusing on the development and implementation of a novel framework called VAE-GPT. Our architecture combines Variational Autoencoder (VAE) and Generative Pre-trained Transformer (GPT), to generate high-quality medical reports. The VAE component enables the model to learn a latent space representation of the images, capturing the underlying patterns and structures. The GPT component leverages the power of transformer-based language models to generate coherent and contextually relevant text. Additionally, a novel metric, Medical Embeddings Attention Distance (MEAD), is proposed in order to capture the semantic similarity between the generated and training medical reports, taking into account the importance of specific words determined by the attention module. Experiments on real dataset demonstrate that our framework achieves state-of-the-art comparable performances in generating accurate and informative medical reports. |
|---|---|
| AbstractList | This paper presents a comprehensive exploration of integrating artificial intelligence (AI) in the healthcare sector, focusing on the development and implementation of a novel framework called VAE-GPT. Our architecture combines Variational Autoencoder (VAE) and Generative Pre-trained Transformer (GPT), to generate high-quality medical reports. The VAE component enables the model to learn a latent space representation of the images, capturing the underlying patterns and structures. The GPT component leverages the power of transformer-based language models to generate coherent and contextually relevant text. Additionally, a novel metric, Medical Embeddings Attention Distance (MEAD), is proposed in order to capture the semantic similarity between the generated and training medical reports, taking into account the importance of specific words determined by the attention module. Experiments on real dataset demonstrate that our framework achieves state-of-the-art comparable performances in generating accurate and informative medical reports. |
| Author | Vasile, Andrea Adornetto, Carlo Guzzo, Antonella |
| Author_xml | – sequence: 1 givenname: Carlo surname: Adornetto fullname: Adornetto, Carlo email: carlo.adornetto@unical.it organization: University of Calabria,Rende,Italy – sequence: 2 givenname: Antonella surname: Guzzo fullname: Guzzo, Antonella email: antonella.guzzo@unical.it organization: University of Calabria,Rende,Italy – sequence: 3 givenname: Andrea surname: Vasile fullname: Vasile, Andrea email: andrea.vasile99@gmail.com organization: University of Calabria,Rende,Italy |
| BookMark | eNo1kF1LwzAYRqMoOOf-gRf5A13fJG3TXNbOTWGibPN6pOkbiaxJSauwf-_8ggfOxYFz8VyTCx88EpIymDMGKl1U2zp9cXXo0vpu8YNjriRjcw5czBmIggkOZ2SmpCpFDgKyAvg5mfBSyARkBldkNgzvACcFipViQjbVxxg6PTpDn7B1Rh_oBvsQR7pCj_EkgqefTtO1HtGPdNtrg7QOvnXfyvk3qn1Ld1H7wYbYYRxuyKXVhwFnf5yS1-X9rn5I1s-rx7paJ44xNSYtN1kLTWOA50IYxU5roSiN1aB4w4pGSWNtI0Fa1A0HZVEVMlMFZjnLuZiS29-uQ8R9H12n43H_f4P4Aq0QWQg |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361320 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE/IET Electronic Library IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Xplore url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798350304602 |
| EISSN | 2837-0740 |
| EndPage | 0435 |
| ExternalDocumentID | 10361320 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IF 6IK 6IL 6IM 6IN AAJGR ABLEC ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK IPLJI OCL RIE RIL RNS |
| ID | FETCH-LOGICAL-i119t-d2c4d0bbc02533c91c91d068cfa092b16b97cffb707feab209fe967496e451523 |
| IEDL.DBID | RIE |
| IngestDate | Wed Aug 27 02:24:16 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i119t-d2c4d0bbc02533c91c91d068cfa092b16b97cffb707feab209fe967496e451523 |
| PageCount | 8 |
| ParticipantIDs | ieee_primary_10361320 |
| PublicationCentury | 2000 |
| PublicationDate | 2023-Nov.-14 |
| PublicationDateYYYYMMDD | 2023-11-14 |
| PublicationDate_xml | – month: 11 year: 2023 text: 2023-Nov.-14 day: 14 |
| PublicationDecade | 2020 |
| PublicationTitle | IEEE International Conference on Dependable, Autonomic and Secure Computing (Online) |
| PublicationTitleAbbrev | DASC/PICOM/CBDCOM/CYBERSCITECH |
| PublicationYear | 2023 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0003009183 |
| Score | 1.8871486 |
| Snippet | This paper presents a comprehensive exploration of integrating artificial intelligence (AI) in the healthcare sector, focusing on the development and... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 0428 |
| SubjectTerms | Computer architecture deep learning Focusing GPT healthcare Measurement medical report generation Medical services Semantics Training Transformers VAE |
| Title | Automatic Medical Report Generation via Latent Space Conditioning and Transformers |
| URI | https://ieeexplore.ieee.org/document/10361320 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA5uiHhSceJvcvDaLWlq0xzn5vAwxnBTdhtN8gK9dDK7gf-9L2k38eBBKLT08Cjv6yNf3sv3HiEPJhPaJjaPHOgk8vXbSIFIo0crBWRMOxcmz72P5WSSLRZq2ojVgxYGAMLhM-j6x1DLtyuz8akyjHCReslvi7SkTGux1j6hIpAt4P95VM845kz1hv3ZoDctMLB6g6dhuH0hf-Z-WxiL7s7ar7kqYVkZnfzzg05J50egR6f7peeMHEB5Tl77m2oVOrDSpvxCa3pN697SHgK6LXI6Rn5ZVnSG22WgaNEWTVaW5qWl8x2VRWLYIW-j5_ngJWpGJkQF56qKbGwSy7Q2SGWEMIrjZVmaGZczFWueaiWNc1oy6SDXMVMOVCoTlUKCzCYWF6Rdrkq4JBRBsjHainPmMMqNThBNqR0HbhDG_Ip0vEOWH3VXjOXOF9d_vL8hx97tXsfHk1vSrtYbuCOHZlsVn-v7gOU3hUigsQ |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA46RT2pOPG3OXjtljRZ2xzndEysY7gpu43mF_TSyewG_ve-pN3EgwehkNLDI-TrI1_ey_ceQncqYVJznQXWSB64_G0gDIuCjo6ZSYi01neee0_j4TCZTsWoFqt7LYwxxl8-My336nP5eq6WLlQGHs4iJ_ndRjsdDnYrudYmpMKAL8Afuld1OaZEtB-64157lINrtXv3D374AgZN3cEwZK21vV-dVfzG0j_855SOUPNHoodHm83nGG2Z4gS9dpfl3NdgxXUCBlcEG1fVpR0IeJVnOAWGWZR4DAdmg8Gizuu4LM4KjSdrMgvUsIne-o-T3iComyYEOaWiDHSouCZSKiAzjClB4dEkSpTNiAgljaSIlbUyJrE1mQyJsEZEMReR4cBtQnaKGsW8MGcIA0w6BFthRiz4uZIc8IylpYYqADI7R023ILOPqi7GbL0WF398v0X7g8lLOkufhs-X6MBB4FR9lF-hRrlYmmu0q1Zl_rm48bh-AxB9o_g |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=IEEE+International+Conference+on+Dependable%2C+Autonomic+and+Secure+Computing+%28Online%29&rft.atitle=Automatic+Medical+Report+Generation+via+Latent+Space+Conditioning+and+Transformers&rft.au=Adornetto%2C+Carlo&rft.au=Guzzo%2C+Antonella&rft.au=Vasile%2C+Andrea&rft.date=2023-11-14&rft.pub=IEEE&rft.eissn=2837-0740&rft.spage=0428&rft.epage=0435&rft_id=info:doi/10.1109%2FDASC%2FPiCom%2FCBDCom%2FCy59711.2023.10361320&rft.externalDocID=10361320 |