Artificial intelligence (AI) and internet of medical things (IoMT) assisted biomedical systems for intelligent healthcare

P Manickam, SA Mariappan, SM Murugesan, S Hansda… - Biosensors, 2022 - mdpi.com
Artificial intelligence (AI) is a modern approach based on computer science that develops
programs and algorithms to make devices intelligent and efficient for performing tasks that …

[HTML][HTML] Artificial intelligence in pharmaceutical technology and drug delivery design

LK Vora, AD Gholap, K Jetha, RRS Thakur, HK Solanki… - Pharmaceutics, 2023 - mdpi.com
Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …

Evaluation of artificial intelligence techniques in disease diagnosis and prediction

N Ghaffar Nia, E Kaplanoglu, A Nasab - Discover Artificial Intelligence, 2023 - Springer
A broad range of medical diagnoses is based on analyzing disease images obtained
through high-tech digital devices. The application of artificial intelligence (AI) in the …

[HTML][HTML] Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective

CC Olisah, L Smith, M Smith - Computer Methods and Programs in …, 2022 - Elsevier
Abstract Background and Objective Diabetes mellitus is a metabolic disorder characterized
by hyperglycemia, which results from the inadequacy of the body to secrete and respond to …

Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture

LP Joseph, EA Joseph, R Prasad - Computers in Biology and Medicine, 2022 - Elsevier
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …

Popular deep learning algorithms for disease prediction: a review

Z Yu, K Wang, Z Wan, S Xie, Z Lv - Cluster Computing, 2023 - Springer
Due to its automatic feature learning ability and high performance, deep learning has
gradually become the mainstream of artificial intelligence in recent years, playing a role in …

Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective

Y Zou, Z Chu, J Guo, S Liu, X Ma, J Guo - Biosensors and Bioelectronics, 2023 - Elsevier
Diabetes and its complications are seriously threatening the health and well-being of
hundreds of millions of people. Glucose levels are essential indicators of the health …

[HTML][HTML] An assessment of machine learning models and algorithms for early prediction and diagnosis of diabetes using health indicators

V Chang, MA Ganatra, K Hall, L Golightly, QA Xu - Healthcare Analytics, 2022 - Elsevier
Breakthroughs in healthcare analytics can help both the doctor and the patient. Analytics in
healthcare can help spot and diagnose diseases early on. Therefore, they can also be used …

[HTML][HTML] Performance analysis of cost-sensitive learning methods with application to imbalanced medical data

ID Mienye, Y Sun - Informatics in Medicine Unlocked, 2021 - Elsevier
Many real-world machine learning applications require building models using highly
imbalanced datasets. Usually, in medical datasets, the healthy patients or samples are …

[HTML][HTML] An unsupervised cluster-based feature grouping model for early diabetes detection

MM Hassan, S Mollick, F Yasmin - Healthcare Analytics, 2022 - Elsevier
Diabetes mellitus is often a hyperglycemic condition that poses a substantial threat to human
health. Early diabetes detection decreases morbidity and mortality. Due to the scarcity of …