TY - JOUR
T1 - Clinical and translational mode of single-cell measurements
T2 - An artificial intelligent single cell
AU - Wang, Xiangdong
AU - Powell, Charles A.
AU - Ma, Qin
AU - Fan, Jia
N1 - Publisher Copyright:
© 2024 The Author(s). Clinical and Translational Discovery published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.
PY - 2024/8
Y1 - 2024/8
N2 - With rapid development and mature of single-cell measurements, single-cell biology and pathology become an emerging discipline to understand the disease. However, it is important to address concerns raised by clinicians as to how to apply single-cell measurements for clinical practice, translate the signals of single-cell systems biology into determination of clinical phenotype, and predict patient response to therapies. The present Perspective proposes a new system coined as the clinical artificial intelligent single-cell (caiSC) with the dynamic generator of clinical single-cell informatics, artificial intelligent analysers, molecular multimodal reference boxes, clinical inputs and outs, and AI-based computerization. This system provides reliable and rapid information for impacting clinical diagnoses, monitoring, and prediction of the disease at the single-cell level. The caiSC represents an important step and milestone to translate the single-cell measurement into clinical application, assit clinicians’ decision-making, and improve the quality of medical services. There is increasing evidence to support the possibility of the caiSC proposal, since the corresponding biotechnologies associated with caiSCs are rapidly developed. Therefore, we call the special attention and efforts from various scientists and clinicians on the caiSCs and believe that the appearance of the caiSCs can shed light on the future of clinical molecular medicine.
AB - With rapid development and mature of single-cell measurements, single-cell biology and pathology become an emerging discipline to understand the disease. However, it is important to address concerns raised by clinicians as to how to apply single-cell measurements for clinical practice, translate the signals of single-cell systems biology into determination of clinical phenotype, and predict patient response to therapies. The present Perspective proposes a new system coined as the clinical artificial intelligent single-cell (caiSC) with the dynamic generator of clinical single-cell informatics, artificial intelligent analysers, molecular multimodal reference boxes, clinical inputs and outs, and AI-based computerization. This system provides reliable and rapid information for impacting clinical diagnoses, monitoring, and prediction of the disease at the single-cell level. The caiSC represents an important step and milestone to translate the single-cell measurement into clinical application, assit clinicians’ decision-making, and improve the quality of medical services. There is increasing evidence to support the possibility of the caiSC proposal, since the corresponding biotechnologies associated with caiSCs are rapidly developed. Therefore, we call the special attention and efforts from various scientists and clinicians on the caiSCs and believe that the appearance of the caiSCs can shed light on the future of clinical molecular medicine.
KW - gene sequencing
KW - genome function
KW - heterogeneity
KW - mechanical phenotypes
KW - single-cell biology
UR - http://www.scopus.com/inward/record.url?scp=85200674745&partnerID=8YFLogxK
U2 - 10.1002/ctd2.353
DO - 10.1002/ctd2.353
M3 - Editorial
AN - SCOPUS:85200674745
SN - 2768-0622
VL - 4
JO - Clinical and Translational Discovery
JF - Clinical and Translational Discovery
IS - 4
M1 - e353
ER -