Alternatives and similar repositories for VQA-Med-2020

Users that are interested in VQA-Med-2020 are comparing it to the libraries listed below

• abachaa / VQA-Med-2019
  Visual Question Answering in the Medical Domain VQA-Med 2019
  ☆92Updated last year
• sergiotasconmorales / consistency_vqa
  Repository of paper Consistency-preserving Visual Question Answering in Medical Imaging (MICCAI2022)
  ☆24Updated 2 years ago
• VirajBagal / MMBERT
  MMBERT: Multimodal BERT Pretraining for Improved Medical VQA
  ☆38Updated 4 years ago
• rayruizhiliao / mutual_info_img_txt
  Joint learning of images and text via maximization of mutual information
  ☆19Updated 3 years ago
• wjhou / ORGan
  Code for the paper "ORGAN: Observation-Guided Radiology Report Generation via Tree Reasoning" (ACL'23).
  ☆54Updated last year
• wjhou / Recap
  Code for the paper "RECAP: Towards Precise Radiology Report Generation via Dynamic Disease Progression Reasoning" (EMNLP'23 Findings).
  ☆27Updated 5 months ago
• rajpurkarlab / CXR-ReDonE
  Official PyTorch implementation of https://arxiv.org/abs/2210.06340 (NeurIPS ‘22)
  ☆21Updated 3 years ago
• ysmiura / ifcc
  The code of Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation
  ☆90Updated 3 years ago
• baeseongsu / ehrxqa
  EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images, NeurIPS 2023 D&B
  ☆86Updated last year
• cs-jerhuang / P-VQA
  Medical Knowledge-Based Network For Patient-oriented Visual Question Answering
  ☆18Updated 2 years ago
• sergiotasconmorales / locvqa
  Localized questions for VQA
  ☆11Updated 6 months ago
• chenzcv7 / MOTOR
  ☆21Updated 2 years ago
• leotam / MIMIC-CXR-annotations
  ☆12Updated 5 years ago
• Awenbocc / med-vqa
  Medical Visual Question Answering via Conditional Reasoning [ACM MM 2020]
  ☆62Updated 4 years ago
• AI-in-Health / Patient-Instructions
  [NeurIPS 2022] Code for "Retrieve, Reason, and Refine: Generating Accurate and Faithful Discharge/Patient Instructions"
  ☆35Updated last year
• sarahESL / PubMedCLIP
  Fine-tuning CLIP using ROCO dataset which contains image-caption pairs from PubMed articles.
  ☆178Updated last year
• baeseongsu / mimic-cxr-vqa
  A new collection of medical VQA dataset based on MIMIC-CXR. Part of the work 'EHRXQA: A Multi-Modal Question Answering Dataset for Electr…
  ☆92Updated last year
• pengfeiliHEU / M2I2
  This repository is made for the paper: Self-supervised vision-language pretraining for Medical visual question answering
  ☆40Updated 2 years ago
• zhjohnchan / ARL
  [ACMMM-2022] This is the official implementation of Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Know…
  ☆37Updated 2 years ago
• allenai / medicat
  Dataset of medical images, captions, subfigure-subcaption annotations, and inline textual references
  ☆163Updated 3 months ago
• nlpaueb / bioCaption
  Diagnostic Captioning
  ☆25Updated 2 years ago
• jbdel / vilmedic
  ViLMedic (Vision-and-Language medical research) is a modular framework for vision and language multimodal research in the medical field
  ☆183Updated last month
• GanjinZero / RAMM
  Codes and Pre-trained models for RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training [ACM MM 202…
  ☆30Updated 2 years ago
• ChantalMP / RaDialog_v2
  LLaVa Version of RaDialog
  ☆24Updated 5 months ago
• MoMarky / radiology-report-extraction
  Extract the findings and impression section of the radiology reports in the MIMIC-CXR-Report and OpenI datasets.
  ☆25Updated 2 years ago
• microsoft / chexprompt
  Expert-level AI radiology report evaluator
  ☆34Updated 7 months ago
• batmanlab / AGXNet
  ☆26Updated 3 years ago
• aioz-ai / MICCAI19-MedVQA
  AIOZ AI - Overcoming Data Limitation in Medical Visual Question Answering (MICCAI 2019)
  ☆65Updated 2 years ago
• aioz-ai / MICCAI21_MMQ
  Multiple Meta-model Quantifying for Medical Visual Question Answering (MICCAI 2021)
  ☆36Updated 3 years ago
• abachaa / VQA-Med-2021
  VQA-Med 2021
  ☆21Updated 3 years ago