Performance of Multimodal Artificial Intelligence Chatbots Evaluated on Clinical Oncology Cases
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.Multimodal artificial intelligence (AI) chatbots were not more accurate than text-only AI chatbots for clinical oncology cases. Further research is needed to improve multimodal AI accuracy in oncology diagnostics.
Area Of Science
- Artificial Intelligence in Medicine
- Oncology Diagnostics
- Medical Chatbot Technology
Background
- Multimodal artificial intelligence (AI) chatbots can process both image and text data, potentially enhancing diagnostic accuracy compared to unimodal (text-only) AI.
- The comparative medical accuracy of multimodal versus unimodal AI chatbots in clinical oncology remains under-investigated.
Purpose Of The Study
- To assess the accuracy of multimodal and unimodal AI chatbots in responding to clinical oncology case questions.
- To evaluate the impact of prompt engineering techniques, specifically zero-shot chain-of-thought, on chatbot performance.
Main Methods
- A cross-sectional study evaluated 10 AI chatbots (3 multimodal, 7 unimodal) using 79 clinical oncology cases from JAMA Network Learning.
- Medical accuracy was benchmarked using multiple-choice and free-text responses.
- Free-text responses were assessed by a panel of oncology specialists.
Main Results
- No consistent superiority in accuracy was found for multimodal chatbots over unimodal chatbots.
- Top performance varied between multiple-choice (up to 72.15%) and free-text (up to 37.97%) evaluations.
- Multimodal chatbot accuracy decreased with cases involving multiple images, and 9 out of 10 chatbots showed lower accuracy in free-text compared to multiple-choice formats.
Conclusions
- Multimodal AI chatbots did not demonstrate superior medical accuracy compared to unimodal chatbots for clinical oncology cases in this study.
- Optimization is needed for multimodal AI to effectively integrate image data for improved oncology-specific accuracy and reliability.
- Further research is essential to enhance the clinical utility of AI in oncology.
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
Related Concept Videos
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Efficient Information Management: NCIS is designed to manage patient information efficiently, making it easily accessible to...
Cancer therapies are various modes of treatment, such as surgery, radiation therapy, and chemotherapy that are administered to cancer patients.
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...