Hybrid fuzzy AHP–TOPSIS approach to prioritizing solutions for inverse reinforcement learning
V Kukreja - Complex & Intelligent Systems, 2023 - Springer
Reinforcement learning (RL) techniques nurture building up solutions for sequential
decision-making problems under uncertainty and ambiguity. RL has agents with a reward …
decision-making problems under uncertainty and ambiguity. RL has agents with a reward …
Trends and Challenges in harnessing big data intelligence for health care transformation
Big data intelligence is drastically changing healthcare by utilizing large amounts of data to
provide critical insights for decision-making. This includes cleaning, organizing information …
provide critical insights for decision-making. This includes cleaning, organizing information …
Prediction of the age and gender based on human face images based on deep learning algorithm
S Haseena, S Saroja, R Madavan… - … Methods in Medicine, 2022 - Wiley Online Library
In recent times, nutrition recommendation system has gained increasing attention due to
their need for healthy living. Current studies on the food domain deal with a …
their need for healthy living. Current studies on the food domain deal with a …
Detection of cancer cells with selective photonic crystal fiber based on fuzzy logic
In this paper, a photonic crystal fiber sensor based on surface plasmon resonance (PCF-
SPR) is proposed for diagnosis of cancer cells. Cells refractive index (RI) detection is in the …
SPR) is proposed for diagnosis of cancer cells. Cells refractive index (RI) detection is in the …
[HTML][HTML] A Neutrosophic differential equation approach for modelling glucose distribution in the bloodstream using neutrosophic sets
Neutrosophic sets are a generalization of fuzzy sets and intuitionistic fuzzy sets. They play
an important role in addressing uncertainty, vagueness, and indeterminacy in problem …
an important role in addressing uncertainty, vagueness, and indeterminacy in problem …
A Novel Early Detection and Prevention of Coronary Heart Disease Framework Using Hybrid Deep Learning Model and Neural Fuzzy Inference System
B Ramesh, K Lakshmanna - IEEE Access, 2024 - ieeexplore.ieee.org
Diabetes is the “mother of all diseases” as it affects multiple organs of body of an individual
in some way. Its timely detection and management are critically important. Otherwise, the …
in some way. Its timely detection and management are critically important. Otherwise, the …
[HTML][HTML] Fuzzy rule based classifier model for evidence based clinical decision support systems
K Navin, M Krishnan - Intelligent Systems with Applications, 2024 - Elsevier
Clinicians benefit from the use of artificial intelligence and machine learning techniques
applied to health data within health records, which identify commonalities between them. It …
applied to health data within health records, which identify commonalities between them. It …
[HTML][HTML] On the notion of fuzzy dispersion measure and its application to triangular fuzzy numbers
In this paper, based on the analysis of the most widely used dispersion measure in the real
context (namely, the variance), we introduce the notion of fuzzy dispersion measure …
context (namely, the variance), we introduce the notion of fuzzy dispersion measure …
A proposed approach for diabetes diagnosis using neuro-fuzzy technique
Diabetes is a chronic disease characterized by a decrease in pancreatic insulin production.
The immune system will be harmed due to this condition, which will raise blood sugar levels …
The immune system will be harmed due to this condition, which will raise blood sugar levels …
FMEA in smartphones: A fuzzy approach
Smartphones are attracting increasing interest due to how they are revolutionizing our lives.
On the other hand, hardware and software failures that occur in them are continually …
On the other hand, hardware and software failures that occur in them are continually …