AI in drug discovery and its clinical relevance

R Qureshi, M Irfan, TM Gondal, S Khan, J Wu, MU Hadi… - Heliyon, 2023 - cell.com
The COVID-19 pandemic has emphasized the need for novel drug discovery process.
However, the journey from conceptualizing a drug to its eventual implementation in clinical …

Application of artificial intelligence in drug design: A review

S Singh, N Kaur, A Gehlot - Computers in Biology and Medicine, 2024 - Elsevier
Artificial intelligence (AI) is a field of computer science that involves acquiring information,
develo** rule bases, and mimicking human behaviour. The fundamental concept behind …

Variational quantum classifier for binary classification: Real vs synthetic dataset

D Maheshwari, D Sierra-Sosa, B Garcia-Zapirain - IEEE access, 2021 - ieeexplore.ieee.org
Nowadays, quantum-enhanced methods have been widely studied to solve machine
learning related problems. This article presents the application of a Variational Quantum …

Ecsu-net: an embedded clustering sliced u-net coupled with fusing strategy for efficient intervertebral disc segmentation and classification

A Nazir, MN Cheema, B Sheng, P Li… - … on Image Processing, 2021 - ieeexplore.ieee.org
Automatic vertebra segmentation from computed tomography (CT) image is the very first and
a decisive stage in vertebra analysis for computer-based spinal diagnosis and therapy …

Early prediction of diabetes mellitus using machine learning

G Tripathi, R Kumar - 2020 8th international conference on …, 2020 - ieeexplore.ieee.org
Diabetes mellitus is one of the noxious disease which causes abnormalities of blood
glucose due to the resistance of producing insulin hormone in the body. It affects various …

Appositeness of optimized and reliable machine learning for healthcare: a survey

S Swain, B Bhushan, G Dhiman… - Archives of Computational …, 2022 - Springer
Abstract Machine Learning (ML) has been categorized as a branch of Artificial Intelligence
(AI) under the Computer Science domain wherein programmable machines imitate human …

Evaluation of machine learning methods developed for prediction of diabetes complications: a systematic review

KR Tan, JJB Seng, YH Kwan, YJ Chen… - Journal of diabetes …, 2023 - journals.sagepub.com
Background: With the rising prevalence of diabetes, machine learning (ML) models have
been increasingly used for prediction of diabetes and its complications, due to their ability to …

Optimized hybrid learning for multi disease prediction enabled by lion with butterfly optimization algorithm

AK Dubey - Sādhanā, 2021 - Springer
As there is a rapid growth in healthcare systems and biomedical data. Machine learning
algorithms are utilized in many researches for predicting the risk of the diseases. The major …

Design of privacy preserving model based on clustering involved anonymization along with feature selection

S Srijayanthi, T Sethukarasi - Computers & Security, 2023 - Elsevier
Healthcare services has become a hug transformation due to the number of disease
emerging at presently. Accordingly, enormous amount of data is generated regarding on the …

Deep learning in multimedia healthcare applications: a review

DP Tobon, MS Hossain, G Muhammad, J Bilbao… - Multimedia …, 2022 - Springer
The increase in chronic diseases has affected the countries' health system and economy.
With the recent COVID-19 virus, humanity has experienced a great challenge, which has led …