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A comprehensive review on artificial intelligence assisted technologies in food industry
Due to escalating food demand in tandem with the growing global population over the past
few decades, artificial intelligence (AI) has been implemented into food business. The ability …
few decades, artificial intelligence (AI) has been implemented into food business. The ability …
Fuzzy logic and hybrid based approaches for the risk of heart disease detection: state-of-the-art review
J Kaur, BS Khehra - Journal of The Institution of Engineers (India): Series B, 2022 - Springer
Abstract Artificial Intelligence, Machine Learning, Fuzzy Logic, Neural Network, Genetic
Algorithm and their hybrid systems play vital role in the medical sciences to diagnose …
Algorithm and their hybrid systems play vital role in the medical sciences to diagnose …
[HTML][HTML] Fuzzy neural network expert system with an improved Gini index random forest-based feature importance measure algorithm for early diagnosis of breast …
Breast cancer is one of the common malignancies among females in Saudi Arabia and has
also been ranked as the one most prevalent and the number two killer disease in the …
also been ranked as the one most prevalent and the number two killer disease in the …
Machine learning predictive models for coronary artery disease
Coronary artery disease (CAD) is the commonest type of heart disease and over 80% of the
deaths resulted from the diseases occurred in develo** countries including Nigeria, with …
deaths resulted from the diseases occurred in develo** countries including Nigeria, with …
[HTML][HTML] Mathematical analysis of COVID-19 by using SIR model with convex incidence rate
R ud Din, EA Algehyne - Results in physics, 2021 - Elsevier
This paper is about a new COVID-19 SIR model containing three classes; Susceptible S (t),
Infected I (t), and Recovered R (t) with the Convex incidence rate. Firstly, we present the …
Infected I (t), and Recovered R (t) with the Convex incidence rate. Firstly, we present the …
Integration of type-2 fuzzy logic and Dempster–Shafer Theory for accurate inference of IoT-based health-care system
The patient's heterogeneous data in IoT-based healthcare system are gathered using
various sensor nodes. the existing healthcare and monitoring systems are mostly based on …
various sensor nodes. the existing healthcare and monitoring systems are mostly based on …
CNN-LSTM deep learning based forecasting model for COVID-19 infection cases in Nigeria, South Africa and Botswana
Background COVID-19 pandemic has indeed plunged the global community especially
African countries into an alarming difficult situation culminating into a great deal amounts of …
African countries into an alarming difficult situation culminating into a great deal amounts of …
Predictive analytics for mortality: FSRNCA-FLANN modeling using public health inventory records
Predictive analytics involves the use of Artificial Intelligence (AI) and Machine Learning (ML)
techniques to analyze current and historical data, identify patterns, and make predictions …
techniques to analyze current and historical data, identify patterns, and make predictions …
Diagnosis of heart diseases: A fuzzy-logic-based approach
Cardiovascular diseases (CVD) also known as heart disease are now the leading cause of
death in the world. This paper presents research for the design and creation of a fuzzy logic …
death in the world. This paper presents research for the design and creation of a fuzzy logic …
Learning features using an optimized artificial neural network for breast cancer diagnosis
Breast cancer (BC) has been one of the significant causes of death worldwide, and its early
detection can play a vital role in increasing the survival rate of this disease. This paper …
detection can play a vital role in increasing the survival rate of this disease. This paper …