Deep Learning in Disease Diagnosis: Models and Datasets

Title:Deep Learning in Disease Diagnosis: Models and Datasets

Volume: 16 Issue: 5

Author(s): Deeksha Saxena, Mohammed Haris Siddiqui and Rajnish Kumar*

Affiliation:

• Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow, Uttar Pradesh,India

Keywords: Artificial neural network, deep learning, data types, machine learning, prediction models, supervised learning.

Abstract:

Background: Deep learning (DL) is an Artificial neural network-driven framework with multiple levels of representation for which non-linear modules combined in such a way that the levels of representation can be enhanced from lower to a much abstract level. Though DL is used widely in almost every field, it has largely brought a breakthrough in biological sciences as it is used in disease diagnosis and clinical trials. DL can be clubbed with machine learning, but at times both are used individually as well. DL seems to be a better platform than machine learning as the former does not require an intermediate feature extraction and works well with larger datasets. DL is one of the most discussed fields among scientists and researchers these days for diagnosing and solving various biological problems. However, deep learning models need some improvisation and experimental validations to be more productive.

Objective: To review the available DL models and datasets that are used in disease diagnosis.

Methods: Available DL models and their applications in disease diagnosis were reviewed discussed and tabulated. Types of datasets and some of the popular disease-related data sources for DL were highlighted.

Results: We have analyzed the frequently used DL methods, data types, and discussed some of the recent deep learning models used for solving different biological problems.

Conclusion: The review presents useful insights about DL methods, data types, and selection of DL models for the disease diagnosis.

Cite this article as:

Saxena Deeksha , Siddiqui Haris Mohammed and Kumar Rajnish *, Deep Learning in Disease Diagnosis: Models and Datasets, Current Bioinformatics 2021; 16 (5) . https://dx.doi.org/10.2174/1574893615999201002124021