[HTML][HTML] Machine learning as a new tool in neurological disease prevention, diagnosis, and treatment

C Volonté - Exploration of Neuroprotective Therapy, 2023 - explorationpub.com
More than 600 different neurological diseases affect the human population. Some of these
are genetic and can emerge even before birth, and some are caused by defects, infections …

13 Advantages, opportunities, and challenges to drug repurposing

K Sharma, H Shrivastava, A Kumar - Drug Repurposing, 2023 - degruyter.com
Drug repurposing, also known as drug repositioning or drug reprofiling, involves
establishing new therapeutic indications for a clinically well-established drug. The drug …

A Comprehensive Review on Technological Advances in Alternate Drug Discovery Process: Drug Repurposing

M Pola, A Tiwari, PD Chandrasai - Current Trends in Biotechnology and …, 2023 - abap.co.in
The traditional de novo drug discovery is time consuming, costly and in some instances the
drugs will fail to treat the disease which result in a huge loss to the organization. Drug …

Using Transfer Learning to Leverage Large Un-labelled Datasets to Improve Classification Models in Cases With Small-Labelled Datasets: Application to Paediatric …

PM Mwaniki - 2023 - erepository.uonbi.ac.ke
Diagnostic and prognostic models based on machine learning models can improve
diagnosis and identification of patients at risk of adverse health outcomes. Healthcare …

[PDF][PDF] The Role of AI and IoT in Healthcare for the Elderly [Diabetes and Covid-19 as a model]: Literature Review

AH Najim, N NASRI - Bilad Alrafidain Journal for Engineering Science and …, 2023 - iasj.net
Recent challenges in the medical field have emphasized the need to exploit new
technology, starting with the production of medicines and medical devices, to electronic …

A materials science-inspired paradigm to predict the physical stability of amorphous drugs

T Barnard - 2023 - wrap.warwick.ac.uk
Amorphous drugs have gained attention as a promising alternative to crystalline
formulations due to their ability to enhance solubility. However, ensuring the physical …

An Empirical Review of Machine Learning Algorithms in the Medical Domain

K Abhishek, V Perni - … in Bio-Medical Image Processing and …, 2023 - igi-global.com
Diseases like diabetes, heart disease, kidney disease, thyroid disease, and other diseases
are increasing in frequency, and people are suffering globally. Specifically, thyroid and heart …

[PDF][PDF] Artificial Intelligence and Machine Learning in the Pharmaceutical Industry

A rights are reserved by Sakshi, V Dashpute - researchgate.net
ABSTRACT The incorporation of Artificial Intelligence (AI) in the pharmaceutical industry has
transformed many elements of drug discovery, development, manufacturing, clinical trials …

[PDF][PDF] Deep Learning in Drug Repurposing: A Review of the CoV-DrugX Module within the CoV-DrugX Pipeline

BR Gautam, K Rawal - osf.io
A comprehensive overview of the integration of deep learning techniques in drug
repurposing, particularly focusing on the CoV-DrugX module within the CoV-DrugX Pipeline …

22. Utilizing artificial intelligence for precision medicine in HIV treatment: predictive modeling and drug repurposing

MBT Tali, CDJ Mbouna, FF Boyom… - Part I: About the … - researchgate.net
Managing the human immunodeficiency virus (HIV) infection poses significant challenges
due to its complex genetic diversity and evolving drug resistance patterns. Artificial …