医生AI？老年患者常见问题AI回答初步研究

数据集获取（Figshare）

• 源站标题：Table 1_Doctor AI? A pilot study examining responses of artificial intelligence to common questions asked by geriatric patients.docx
• DOI：10.3389/frai.2024.1438012.s001
• 发布日期：2024-07-25
• 文件数：1 个
• 文件总体积：29.05 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_1_Doctor_AI_A_pilot_study_examining_responses_of_artificial_intelligence_to_common_questions_asked_by_geriatric_patients_docx/26369317

命令行下载

curl -L -o "Table 1_Doctor AI? A pilot study examining responses of artificial intelligence to common questions asked by geriatric patients.docx" "https://ndownloader.figshare.com/files/47915194"

文件清单

• Table 1_Doctor AI? A pilot study examining responses of artificial intelligence to common questions asked by geriatric patients.docx（29.05 KB）

文件总体积 29.05 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

IntroductionAI technologies have the potential to transform patient care. AI has been used to aid in differential diagnosis and treatment planning for psychiatric disorders, administer therapeutic protocols, assist with interpretation of cognitive testing, and patient treatment planning. Despite advancements, AI has notable limitations and remains understudied and further research on its strengths and limitations in patient care is required. This study explored the responses of AI (Chat-GPT 3.5) and trained clinicians to commonly asked patient questions.
MethodsThree clinicians and AI provided responses to five dementia/geriatric healthcare-related questions. Responses were analyzed by a fourth, blinded clinician for clarity, accuracy, relevance, depth, and ease of understanding and to determine which response was AI generated.
ResultsAI responses were rated highest in ease of understanding and depth across all responses and tied for first for clarity, accuracy, and relevance. The rating for AI generated responses was 4.6/5 (SD = 0.26); the clinician s’’ responses were 4.3 (SD = 0.67), 4.2 (SD = 0.52), and 3.9 (SD = 0.59), respectively. The AI generated answers were identified in 4/5 instances.
ConclusionsAI responses were rated more highly and consistently on each question individually and overall than clinician answers demonstrating that AI could produce good responses to potential patient questions. However, AI responses were easily distinguishable from those of clinicians. Although AI has the potential to positively impact healthcare, concerns are raised regarding difficulties discerning AI from human generated material, the increased potential for proliferation of misinformation, data security concerns, and more.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/frai.2024.1438012.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_1_Doctor_AI_A_pilot_study_examining_responses_of_artificial_intelligence_to_common_questions_asked_by_geriatric_patients_docx/26369317）。