Big hopes for big data
Name: 木村芳華
Student ID: D0740902
Website: https://www.nature.com/articles/s41591-019-0740-8
In the past ten years, the data related to healthcare had been more and more. The amount of data that is available for analysis is astonishing because of the digitization of medical records, the affordability of molecular testing increasing, the emergence of medical informatics, and the widespread use of wearable devices.
The appearance of new technologies has brought innovation and expanded the possibility of clinical research by providing trial participants with new solutions and bringing different people from different fields together. Molecular information is increasingly being incorporated into mainstream oncology to match patients with therapy, which is commonly referred to as "precision medicine." This information provides incredible value for researchers and also new insights into the mechanism of disease and treatment response, increasing the likelihood of recovery.
With such large-scale of data collection and processing, challenges still need to be faced, in the relatively of the recent history, big data has shown that if people ignore these deficiencies can cause terrible consequences for health equity. Computational models can be very powerful, they can coordinate health parameters and increase the granularity of individual health conditions. However, these models must be designed without any prejudice, otherwise, they may exacerbate rather than reduce racial, gender, economic, or geographic medical disparities.
As big data enters clinical care, people are giving it high expectations, of what big data can do for medicine and how will big data enters clinical care changes our lives.
Student ID: D0740902
Website: https://www.nature.com/articles/s41591-019-0740-8
In the past ten years, the data related to healthcare had been more and more. The amount of data that is available for analysis is astonishing because of the digitization of medical records, the affordability of molecular testing increasing, the emergence of medical informatics, and the widespread use of wearable devices.
The appearance of new technologies has brought innovation and expanded the possibility of clinical research by providing trial participants with new solutions and bringing different people from different fields together. Molecular information is increasingly being incorporated into mainstream oncology to match patients with therapy, which is commonly referred to as "precision medicine." This information provides incredible value for researchers and also new insights into the mechanism of disease and treatment response, increasing the likelihood of recovery.
With such large-scale of data collection and processing, challenges still need to be faced, in the relatively of the recent history, big data has shown that if people ignore these deficiencies can cause terrible consequences for health equity. Computational models can be very powerful, they can coordinate health parameters and increase the granularity of individual health conditions. However, these models must be designed without any prejudice, otherwise, they may exacerbate rather than reduce racial, gender, economic, or geographic medical disparities.
As big data enters clinical care, people are giving it high expectations, of what big data can do for medicine and how will big data enters clinical care changes our lives.
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