Summary of Performance Assessment Of Chatgpt Vs Bard in Detecting Alzheimer’s Dementia, by Balamurali B T et al.
Performance Assessment of ChatGPT vs Bard in Detecting Alzheimer’s Dementia
by Balamurali B T, Jer-Ming Chen
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper assesses the ability of large language models (LLMs) to recognize individuals with Alzheimer’s Dementia (AD) and Cognitively Normal (CN) using textual input from spontaneous speech recordings. The study evaluates three LLM chatbots, ChatGPT-3.5, ChatGPT-4, and Bard, using a zero-shot learning approach at two levels of independent queries. The performance of each chatbot is measured in terms of accuracy, sensitivity, specificity, precision, and F1 score. The results show that the LLM chatbots can identify AD vs CN with higher accuracy than chance, but they do not yet meet clinical application standards. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how well large language models (LLMs) can understand people’s speech to tell if someone has Alzheimer’s Dementia (AD) or is cognitively normal. Researchers tested three LLM chatbots to see how good they are at recognizing AD and CN from recorded conversations. They used a special way of asking the chatbots questions, called zero-shot learning, and measured how well they did. The results show that these chatbots can tell if someone has AD or is cognitively normal better than chance, but they’re not quite good enough for medical use. |
Keywords
» Artificial intelligence » F1 score » Precision » Zero shot
