Application of artificial neural networks in the process analytical technology of pharmaceutical manufacturing—a review
Industry 4.0 has started to transform the manufacturing industries by embracing
digitalization, automation, and big data, aiming for interconnected systems, autonomous …
digitalization, automation, and big data, aiming for interconnected systems, autonomous …
Impact of feature scaling on machine learning models for the diagnosis of diabetes
Due to its high prevalence and incidence, diabetes is considered significant public health.
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …
Predicting and analysing the quality of water resources for industrial purposes using integrated data-intelligent algorithms
JC Egbueri - Groundwater for Sustainable Development, 2022 - Elsevier
The continuous increase in the rate of industrialization in developing countries, in recent
times, calls for continuous industrial water quality assessment and prediction. This is to …
times, calls for continuous industrial water quality assessment and prediction. This is to …
Incorporation of information entropy theory, artificial neural network, and soft computing models in the development of integrated industrial water quality index
JC Egbueri - Environmental Monitoring and Assessment, 2022 - Springer
Keeping purpose and targeted end-users in perspective, several water quality indices have
been developed over the past decades to summarily convey water quality information to …
been developed over the past decades to summarily convey water quality information to …
An overview of streamflow prediction using random forest algorithm
Since the first application of Artificial Intelligence in the field of hydrology, there has been a
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
great deal of interest in exploring aspects of future enhancements to hydrology. This is …
The effect of ethanolic leaves extract of Hymenodictyon floribundun on inflammatory biomarkers: a data-driven approach
Background Medicinal plants are used to manage pain and inflammatory disorders in
traditional medicine. A scientific investigation could serve as a basis for the determination of …
traditional medicine. A scientific investigation could serve as a basis for the determination of …
Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients
Co-processing (CP) provides superior properties to excipients and has become a reliable
option to facilitated formulation and manufacturing of variety of solid dosage forms …
option to facilitated formulation and manufacturing of variety of solid dosage forms …
Clinical modelling of RVHF using pre-operative Variables: a direct and inverse feature extraction technique
Right ventricular heart failure (RVHF) mostly occurs due to the failure of the left-side of the
heart. RVHF is a serious disease that leads to swelling of the abdomen, ankles, liver …
heart. RVHF is a serious disease that leads to swelling of the abdomen, ankles, liver …
[HTML][HTML] Revolutionizing drug discovery: The impact of artificial intelligence on advancements in pharmacology and the pharmaceutical industry
To create novel treatments and treat complex diseases, the pharmaceutical sector is
essential. Drug discovery, however, is a time-consuming, pricey, and dangerous endeavor …
essential. Drug discovery, however, is a time-consuming, pricey, and dangerous endeavor …
Review of machine learning algorithms application in pharmaceutical technology
Abstract Machine learning algorithms, and artificial intelligence in general, have a wide
range of applications in the field of pharmaceutical technology. Starting from the formulation …
range of applications in the field of pharmaceutical technology. Starting from the formulation …