Application of Bayesian Approach in Cancer Clinical Trial
By Atanu Bhattacharjee. 2014
19 citations recorded by the source corpus.
The application of Bayesian approach in clinical trials becomes more useful over classical method. It is beneficial from design to analysis phase. The straight forward statement is possible to obtain through Bayesian about the drug treatment effect. Complex computational problems are simple to handle with Bayesian techniques. The technique is only feasible to performing presence of prior information of the data. The inference is possible to establish through posterior estimates. However, some limitations are present in this method. The objective of this work was to explore the several merits and demerits of Bayesian approach in cancer research. The review of the technique will be helpful for the clinical researcher involved in the oncology to explore the limitation and power of Bayesian techniques.
Subfields: Cancer Research, Molecular Biology, Statistics and Probability
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In Molecular Biology
- Syuzo Kaneko
- Masaaki Komatsu
- Ken Asada
- Ken Takasawa
- Amina Bolatkan
- Jun Sese
- Ryuji Hamamoto
- Yusuke Nakamura
Citations in the corpus
- Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine (2020, methodology): “In the era of big data, the Bayesian statistical approach is better suited for combining the current data with prior knowledge and for creating posterior probabilities for both drug effectiveness and its safety [153].”