Using Semi-supervised Learning for the Creation of Medical Systematic Review: An exploratory Analysis

In this research, we explore semi-supervised learning based classifiers to identify articles that can be included when creating medical systematic reviews (SRs). Specifically, we perform comparative study of various semi-supervised learning algorithm, and identify the best technique that is suited for SRs creation. We also aim to identify whether semisupervised learning technique with few labeled samples produce meaningful work saving for SRs creation. Through an empirical study, we demonstrate that semi-supervised classifiers are viable for selecting articles for systematic reviews and situations when only a few numbers of training samples are available

Using semi-supervised learning for the creation of medical systematic review: An exploratory analysis

In this research, we explore semi-supervised learning based classifiers to identify articles that can be included when creating medical systematic reviews (SRs). Specifically, we perform comparative study of various semi-supervised learning algorithm, and identify the best technique that is suited for SRs creation. We also aim to identify whether semisupervised learning technique with few labeled samples produce meaningful work saving for SRs creation. Through an empirical study, we demonstrate that semi-supervised classifiers are viable for selecting articles for systematic reviews and situations when only a few numbers of training samples are available

An Application of Data Analysis and Data Mining for Multiple Disease Prediction through the Use of Fuzzy Logic

Medical systems use text mining which have providing facility of health condition monitoring and disease modeling. Medical system work on the PHI of the patient or user. PHI means personal health information. System helps to store data at one place like disease precaution and healthcare. The successful application of data mining found in highly visible fields such as e-business, commerce and trade has led to its application in other firm

Knowledge-based Biomedical Data Science 2019

Knowledge-based biomedical data science (KBDS) involves the design and implementation of computer systems that act as if they knew about biomedicine. Such systems depend on formally represented knowledge in computer systems, often in the form of knowledge graphs. Here we survey the progress in the last year in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as on approaches for creating knowledge graphs. Major themes include the relationships between knowledge graphs and machine learning, the use of natural language processing, and the expansion of knowledge-based approaches to novel domains, such as Chinese Traditional Medicine and biodiversity.Comment: Manuscript 43 pages with 3 tables; Supplemental material 43 pages with 3 table

An Efficient Medical Text Mining in Diseases Diagnoses And its equivalent Data privacy Preservation Policy for Medical Data: A Review

Healthcare systems use a medical text mining which have been increasingly facilitating health condition monitoring and disease modeling. System works on the Personal Health Information (PHI) of the user. Healthcare system grant users access to range of health information and medical knowledge. Benefit of the system is all the information about disease, precautions and healthcare are store at one place. Unfortunately, delegating both storage and computation to the untreated entity would bring a series of security and privacy issues. One of the controversial issues for PHI is how the technology could threaten the privacy of patient health information. The proposed system focused on fine-grained privacy-preserving static medical text access and analysis, which can hardly afford the dynamic health condition fluctuation

Development Of Database And Computational Methods For Disease Detection And Drug Discovery

Ph.DDOCTOR OF PHILOSOPH

Bioinformatics Analysis and Modelling of Therapeutically Relevant Molecules

Ph.DDOCTOR OF PHILOSOPH

Biointormatics of Targeted Therapeutics And Applications in Drug Discovery

Ph.DDOCTOR OF PHILOSOPH

Development of Virtual Screening and In Silico Biomarker Identification Model for Pharmaceutical Agents

Ph.DDOCTOR OF PHILOSOPH