Application of Big Medical Data in Precision Medicine
Thanks to the massive amount of data collected from clinical, biomolecular and health research, the field of precision medicine has experienced significant growth. The Electronic Medical Record system has been widely adopted to capture and store large volumes of clinical data, including screening, diagnostic, biochemical testing, imaging, treatment results, and follow-ups, as well as medical and family histories. Furthermore, advanced technologies shorten the length of time needed into days and even hours to collect biomolecular data from studies in genomics, transcriptomics, proteomics, epigenomics, metabolomics, metagenomics, and exposomics, collectively termed "-omics", dramatically speeding up clinical analysis. “Multi-omics” molecular data from these research studies are broadly used in precision medicine and related clinical applications, constituting one of the fastest-growing databases in biomedicine. Moreover, wearable devices and smartphones collect biological data on personal health continuously. To utilize these multidimensional data for exploring the mystery of tumor and disease, effective algorithms and application methods are demanded.
To further our understanding in the abovementioned topics, we encourage the submission of manuscripts on all aspects of big medical data application in precision medicine, its statistical analysis algorithm, machine learning, artificial intelligence, and biology experiments in vivo and vitro. We accept reviews, conference proceedings, and short- and full-size research papers.
Prof. Dr. Yi Zhao
Prof. Dr. Jinpu Yu
Dr. Haifeng Zhang
Dr. Min Hu
Dr. Jincheng Guo
- multiomics molecular markers
- natural drug targets
- tumor immunotherapy
- artificial intelligence
- machine learning
- image recognition
|Journal Name||Impact Factor||CiteScore||Launched Year||First Decision (median)||APC|
|4.2||4.0||2012||18.8 Days||CHF 2700|
|5.2||7.4||2009||18.2 Days||CHF 2900|
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