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Digital Model for Diagnosis of Postoperative Complications in Medicine Using Bioinformatics: Evaluate and Predict the Patient's Condition
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| Author: | Горбаченко Владимир Иванович | |
| Annotation: | Digital models are needed in medicine using bioinformatics for diagnosis and prediction. Such models are especially needed in personalized medicine using bioinformatics. In this area, it is necessary to evaluate and predict the patient's condition from a priori knowledge obtained from other patients. Therefore, a new direction appeared - predictive medicine using bioinformatics. Predictive medicine, or “in silico medicine” is the use of computer modelling and intelligent technologies in the diagnosis, treatment and prevention of diseases. Using predictive medicine, the doctor can determine the likelihood of the development of certain diseases and choose the optimal treatment using bioinformatics. Predictive medicine begins to be applied in surgery. The prognosis in surgery consists in the preoperative evaluation of various surgical interventions and in the evaluation of possible outcomes of surgical interventions. | |
| Type: | Article | |
| Kind: | Electronic copy | |
| Parts: | 1 | |
| The year of publishing: | 2019 | |
| Publishing house: | IGI Global, Hershey, PA, USA | |
| The target audience: | Researcher | |
| Special purpose: | Scientific | |
| Copyright holder: | IGI Global | |
| ISSN: | 2640-0324 | |
| DOI: | 10.4018/IJARB.2019070101 | |
| Bibliographic reference: | Gorbachenko V. Digital Model for Diagnosis of Postoperative Complications in Medicine Using Bioinformatics: Evaluate and Predict the Patient's Condition // International Journal of Applied Research in Bioinformatics (IJARB). — 2019, Vol. 9. — No 2. — P. 1–23. | |
| Url: | https://www.igi-global.com/gateway/article/237197#pnlRecommendationForm | |
| Language: | English | |
| Post date: | 26.11.2020 |