Using Social Robots and AI to Perform Genetic Risk Assessment for Cancer

Genetic risk assessment (GRA) and genetic counseling have become integral to optimal patient care for patients with cancer. At present, there is a limited number of qualified healthcare providers who provide this service. To assist professionals in the GRA process, we have combined social robotics and retrieval-augmented generative artificial intelligence (RAG AI) to provide education related to hereditary cancer to be included in GRA sessions for individuals at risk. This GRA application pushes the boundary on previously available chatbots and AI systems by creating a novel and interactive experience enhanced by professionally verified information. In the future, we seek to improve the app as it is and obtain feedback from both GRA professionals and potential end-users that will be used to enhance the system and provide customized risk assessment. Overall, our GRA system takes the next step towards informing patients of their hereditary cancer risk and pertinent care options.

Authors

Institutions

Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2024-11-08
DOI
https://doi.org/10.1609/aaaiss.v4i1.31817
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using Social Robots and AI to Perform Genetic Risk Assessment for Cancer

Christopher M. Brown, Jeremiah Augustine, Xiaopeng Zhao, Laura M. Enomoto et al.
Proceedings of the AAAI Symposium Series
Artificial Intelligence in Healthcare and Education
article

Using Social Robots and AI to Perform Genetic Risk Assessment for Cancer

Christopher M. Brown, Jeremiah Augustine, Xiaopeng Zhao, Laura M. Enomoto, Tyler Morris, Andrew Ward, Erin Campbell, S.-M. AN
article en

Abstract

Genetic risk assessment (GRA) and genetic counseling have become integral to optimal patient care for patients with cancer. At present, there is a limited number of qualified healthcare providers who provide this service. To assist professionals in the GRA process, we have combined social robotics and retrieval-augmented generative artificial intelligence (RAG AI) to provide education related to hereditary cancer to be included in GRA sessions for individuals at risk. This GRA application pushes the boundary on previously available chatbots and AI systems by creating a novel and interactive experience enhanced by professionally verified information. In the future, we seek to improve the app as it is and obtain feedback from both GRA professionals and potential end-users that will be used to enhance the system and provide customized risk assessment. Overall, our GRA system takes the next step towards informing patients of their hereditary cancer risk and pertinent care options.

Proceedings of the AAAI Symposium SeriesVol. 4(1)
University of Tennessee Medical Center (US), University of Tennessee at Knoxville (US)
Quality Education
Openalex Percentile: Top 85%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Using Social Robots and AI to Perform Genetic Risk Assessment for Cancer — Christopher M. Brown, Jeremiah Augustine, et al. · Proceedings of the AAAI Symposium Series (2024) | TGRS Research Map | TGRS