Clinical and translational mode of single‐cell measurements: An artificial intelligent single cell

Abstract 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.

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Publication Details

Journal
Clinical and Translational Discovery
Published
2024-08-01
DOI
https://doi.org/10.1002/ctd2.353
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.23
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article

Clinical and translational mode of single‐cell measurements: An artificial intelligent single cell

Charles A. Powell, Qin Ma, Xiangdong Wang, Jia Fan
1 citations
Clinical and Translational Discovery
Single-cell and spatial transcriptomics
0.23
article

Clinical and translational mode of single‐cell measurements: An artificial intelligent single cell

Charles A. Powell, Qin Ma, Xiangdong Wang, Jia Fan
article en
1 citations

Abstract

Abstract 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.

Clinical and Translational DiscoveryVol. 4(4)
Shanghai Medical College of Fudan University (CN), Fudan University (CN), Zhongshan Hospital (CN), Shanghai Center For Bioinformation Technology (CN), The Ohio State University (US), Icahn School of Medicine at Mount Sinai (US)
Openalex Percentile: Top 43%
Single-cell and spatial transcriptomics
0.23
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Clinical and translational mode of single‐cell measurements: An artificial intelligent single cell — Charles A. Powell, Qin Ma, et al. · Clinical and Translational Discovery (2024) | TGRS Research Map | TGRS