Summary of Yes, This Is What I Was Looking For! Towards Multi-modal Medical Consultation Concern Summary Generation, by Abhisek Tiwari et al.
Yes, this is what I was looking for! Towards Multi-modal Medical Consultation Concern Summary Generation
by Abhisek Tiwari, Shreyangshu Bera, Sriparna Saha, Pushpak Bhattacharyya, Samrat Ghosh
First submitted to arxiv on: 10 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A new AI system is proposed to generate summaries of patients’ major concerns during doctor-patient consultations. The system, called IR-MMCSG, uses a transformer-based architecture to recognize patients’ intentions and generate a concise summary of their concerns. The approach takes into account nonverbal cues like facial expressions and gestures, as well as patients’ personal information such as age and gender. The system is tested on the MM-MediConSummation corpus, a dataset of annotated patient-doctor consultations that includes medical concern summaries, intents, and other relevant information. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new computer program helps doctors understand what patients are worried about during visits. This program uses artificial intelligence to look at patients’ facial expressions and body language to figure out what’s bothering them. It also considers things like the patient’s age and gender to make sure the doctor is talking about the right medical issue. The goal is to make it easier for doctors to understand their patients and provide better care. |
Keywords
» Artificial intelligence » Transformer
