Big data analytics in precision medicine

Biswas, Saurabh; Hasija, Yasha

doi:10.1016/b978-0-323-91907-4.00005-4

Cited by 3 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The National University of Singapore teaches the compulsory discipline "Bioinformatics and artificial Intelligence in Medicine" for students of the bachelor's degree program in biomedical informatics, during the study of which such issues as natural language processing, computer vision, medical data processing, deep learning are considered (Biswas & Hasija, 2022).…”

Section: Figure 6 Results Of Teachers' Answers To the Question: "In Y...mentioning

confidence: 99%

End-to-end Technologies in Medicine, Pharmacy, Biology

Denisova,

Abramishvili

2024

MEDIN

View full text Add to dashboard Cite

The article raises the topical issue of the use of end-to-end technologies for medicine, pharmacy, and biology. The analysis of the use of new technologies in these areas is carried out at the present time. The authors are looking for ways to solve the problem of teaching humanities and natural sciences at a medical university using the capabilities of modern technologies. A random sampling method using the capabilities of Goole forms was used to conduct a survey of 2nd year students of the medical university and teachers working with them. The level of training, the needs of students for new knowledge on modern end-to-end technologies, and the possibilities of implementing training programs are discussed. The survey showed that despite the widespread introduction of end-to-end technologies, the knowledge of students and teachers in this area is extremely limited. Students have a need to acquire new knowledge that can be applied in their future profession. Several solutions to the problem of teaching student’s new technologies and their practical application in medicine, pharmacy, and biology are proposed. The survey also showed that there are two possible options: 1) the introduction of a separate optional course into the curriculum; 2) teachers can talk about the possibilities of new technologies and their use during the study of the discipline. For effective teaching, teachers must improve their skills in a timely manner by taking courses. With an integrated approach, a quick and effective solution to the task is possible.

show abstract

Section: Figure 6 Results Of Teachers' Answers To the Question: "In Y...mentioning

confidence: 99%

End-to-end Technologies in Medicine, Pharmacy, Biology

Denisova,

Abramishvili

2024

MEDIN

View full text Add to dashboard Cite

show abstract

“…Accuracy: ecision Tree: 86.37% (with cross-validation) and 86.53% (without cross-validation), XGBoost: 86.87% (with cross-validation) and 87.02% (without cross-validation), Random Forest: 87.05% (with cross-validation) and 86.92% (without cross-validation), Multilayer Perceptron: 87.28% (with crossvalidation) and 86.94% (without cross-validation). "Machine Learning-Based Model to Predict Heart Disease in Early Stage Employing Different Feature Selection Techniques" (13) Applied Chi-Square, ANOVA, and Mutual Information for feature selection and Logistic Regression, Support Vector Machine , K-Nearest Neighbor, Random Forest, Naive Bayes, and Decision Tree for classification Mutual Information was identified as most effective one. "Heart Disease Prediction Using Machine Learning" (14) Applied K Nearest Neighbour and Support Vector Machine.…”

Section: Observation 2: Applying Random Forest Classifier and Whale O...mentioning

confidence: 99%

“…It was identified through the proposed work that Mutual Information worked best among other as feature selector. (13) . Taher M. Ghazal et al proposed a heart disease prediction model applying Support Vector Machine and K Nearest Neighbour.…”

Section: Introductionmentioning

confidence: 99%

An Advanced Model to Predict Heart Disease Applying Random Forest Classifier and Whale Optimization Algorithm

Majumder,

Gupta,

Singh

et al. 2023

IJST

View full text Add to dashboard Cite

“…Big data is a term used for complex or large datasets that cannot be accurately processed or stored by traditional management tools. Omics and electronic health record (EHR) data are essential big biomedical data, forming the foundation of PM [3].…”

Section: Introduction: the Growing Field Of Precision Medicinementioning

confidence: 99%

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Muharremi,

Meçani,

Muka

2023

JPM

View full text Add to dashboard Cite

Precision medicine (PM), through the integration of omics and environmental data, aims to provide a more precise prevention, diagnosis, and treatment of disease. Currently, PM is one of the emerging approaches in modern healthcare and public health, with wide implications for health care delivery, public health policy making formulation, and entrepreneurial endeavors. In spite of its growing popularity and the buzz surrounding it, PM is still in its nascent phase, facing considerable challenges that need to be addressed and resolved for it to attain the acclaim for which it strives. In this article, we discuss some of the current methodological pitfalls of PM, including the use of big data, and provide a perspective on how these challenges can be overcome by bringing PM closer to evidence-based medicine (EBM). Furthermore, to maximize the potential of PM, we present real-world illustrations of how EBM principles can be integrated into a PM approach.

show abstract

Big data analytics in precision medicine

Cited by 3 publications

References 14 publications

End-to-end Technologies in Medicine, Pharmacy, Biology

End-to-end Technologies in Medicine, Pharmacy, Biology

An Advanced Model to Predict Heart Disease Applying Random Forest Classifier and Whale Optimization Algorithm

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Contact Info

Product

Resources

About