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Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991–2020)
Understanding the data and reaching accurate conclusions are of paramount importance in
the present era of big data. Machine learning and probability theory methods have been …
the present era of big data. Machine learning and probability theory methods have been …
[HTML][HTML] Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
Uncertainty estimation in healthcare involves quantifying and understanding the inherent
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
An efficient clinical support system for heart disease prediction using TANFIS classifier
J Sekar, P Aruchamy… - Computational …, 2022 - Wiley Online Library
In today's world, the advancement of telediagnostic equipment plays an essential role to
monitor heart disease. The earlier diagnosis of heart disease proliferates the compatibility of …
monitor heart disease. The earlier diagnosis of heart disease proliferates the compatibility of …
Optimized ANFIS model using hybrid metaheuristic algorithms for Parkinson's disease prediction in IoT environment
Throughout recent years, the progress of telemonitoring and telediagnostics devices for
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …
A novel CNN-TLSTM approach for dengue disease identification and prevention using IoT-fog cloud architecture
One of the mosquito-borne pandemic viral infections is Dengue which is mostly transmitted
to humans by the Aedes agypti or female Aedes albopictis mosquitoes. The dengue disease …
to humans by the Aedes agypti or female Aedes albopictis mosquitoes. The dengue disease …
A re-organizing biosurveillance framework based on fog and mobile edge computing
Biological threats are becoming a serious security issue for many countries across the world.
Effective biosurveillance systems can primarily support appropriate responses to biological …
Effective biosurveillance systems can primarily support appropriate responses to biological …
[HTML][HTML] From Data to Diagnosis: Machine Learning Revolutionizes Epidemiological Predictions
The outbreak of epidemiological diseases creates a major impact on humanity as well as on
the world's economy. The consequence of such infectious diseases affects the survival of …
the world's economy. The consequence of such infectious diseases affects the survival of …
Identification of Vector Borne Disease Spread Using Big Data Analysis
Diseases transmitted by vectors are becoming an increasingly serious problem in India. The
prevention and control of these vector-borne diseases continues to be a struggle for the …
prevention and control of these vector-borne diseases continues to be a struggle for the …
2-(dec-2-enyl)-3-methyl quinolin-4-ol-C20H27NO and 7-amino-N-methyl phenazine-1-carboxamide—C14 H13 N4O2: potent bio-active compounds against dengue …
Vector control plays a critical role in achieving reduction in the spread of dengue fever and
dengue haemorrhagic fever among humans. As there are no proper medications for the …
dengue haemorrhagic fever among humans. As there are no proper medications for the …
[PDF][PDF] DEVELOPMENT OF PREDICTION MODEL USING MACHINE LEARNING FOR VECTOR BORNE DISEASES IN INDIA
DEVELOPMENT OF PREDICTION MODEL USING MACHINE LEARNING FOR VECTOR
BORNE DISEASES IN INDIA Page 1 DEVELOPMENT OF PREDICTION MODEL USING …
BORNE DISEASES IN INDIA Page 1 DEVELOPMENT OF PREDICTION MODEL USING …