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 …
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
Health recommender systems development, usage, and evaluation from 2010 to 2022: A scoping review
A health recommender system (HRS) provides a user with personalized medical information
based on the user's health profile. This scoping review aims to identify and summarize the …
based on the user's health profile. This scoping review aims to identify and summarize the …
A systematic review on food recommender systems for diabetic patients
R Yera, AA Alzahrani, L Martínez… - International Journal of …, 2023 - mdpi.com
Recommender systems are currently a relevant tool for facilitating access for online users, to
information items in search spaces overloaded with possible options. With this goal in mind …
information items in search spaces overloaded with possible options. With this goal in mind …
An intelligent fuzzy inference rule‐based expert recommendation system for predictive diabetes diagnosis
P Nagaraj, P Deepalakshmi - International Journal of Imaging …, 2022 - Wiley Online Library
Diabetes is one of the most common and hazardous diseases, which can affect almost every
organ in the body. Diagnosis of diabetes requires determining all vital parameters related to …
organ in the body. Diagnosis of diabetes requires determining all vital parameters related to …
A hybrid imputation method for multi-pattern missing data: A case study on type II diabetes diagnosis
MH Nadimi-Shahraki, S Mohammadi, H Zamani… - Electronics, 2021 - mdpi.com
Real medical datasets usually consist of missing data with different patterns which decrease
the performance of classifiers used in intelligent healthcare and disease diagnosis systems …
the performance of classifiers used in intelligent healthcare and disease diagnosis systems …
[HTML][HTML] Automatic tool segmentation and tracking during robotic intravascular catheterization for cardiac interventions
Background Cardiovascular diseases resulting from aneurism, thrombosis, and
atherosclerosis in the cardiovascular system are major causes of global mortality. Recent …
atherosclerosis in the cardiovascular system are major causes of global mortality. Recent …
Optimal design of type-2 fuzzy systems for diabetes classification based on genetic algorithms
Diabetes has become a global health problem, where a proper diagnosis is vital for the life
quality of patients. In this article, a genetic algorithm is put forward for designing type-2 fuzzy …
quality of patients. In this article, a genetic algorithm is put forward for designing type-2 fuzzy …
[HTML][HTML] The evaluation of health recommender systems: A scoping review
Background People often look online for information about health concerns, but the vast
amount of available and unregulated information can cause misinformation and potential …
amount of available and unregulated information can cause misinformation and potential …
The role of long non-coding RNA UCA1 and MALAT1 in bladder cancer patients
NT Aboelkhair, SS Mashal, SM El-Hefnawy… - Human Gene, 2023 - Elsevier
Background Bladder cancer (BC) is considered the most prevalent tumor of the urinary tract,
and incidence rates are rising globally. Long noncoding RNAs (lncRNAs) can serve as …
and incidence rates are rising globally. Long noncoding RNAs (lncRNAs) can serve as …
Prediction the prognosis of the poisoned patients undergoing hemodialysis using machine learning algorithms
Background Hemodialysis is a life-saving treatment used to eliminate toxins and metabolites
from the body during poisoning. Despite its effectiveness, there needs to be more research …
from the body during poisoning. Despite its effectiveness, there needs to be more research …