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Big data analytics for data-driven industry: a review of data sources, tools, challenges, solutions, and research directions
The study of big data analytics (BDA) methods for the data-driven industries is gaining
research attention and implementation in today's industrial activities, business intelligence …
research attention and implementation in today's industrial activities, business intelligence …
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 …
Nature-inspired computing and machine learning based classification approach for glaucoma in retinal fundus images
Glaucoma, commonly known as the silent thief of sight, is the second most common cause of
blindness in humans, and the number of cases is steadily increasing. Conventional …
blindness in humans, and the number of cases is steadily increasing. Conventional …
Empirical exploration of whale optimisation algorithm for heart disease prediction
Heart Diseases have the highest mortality worldwide, necessitating precise predictive
models for early risk assessment. Much existing research has focused on improving model …
models for early risk assessment. Much existing research has focused on improving model …
Multi-strategy serial cuckoo search algorithm for global optimization
Cuckoo search algorithm (CS) is a simple and effective nature-inspired optimization
algorithm, which has been widely applied to solve the complex engineering optimization …
algorithm, which has been widely applied to solve the complex engineering optimization …
[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 …
Collaboration of features optimization techniques for the effective diagnosis of glaucoma in retinal fundus images
Glaucoma is the second most common cause of vision loss. Manual screening of a patient's
eye or screening through a fundus image of the patient's eye requires expert …
eye or screening through a fundus image of the patient's eye requires expert …
[PDF][PDF] Medical diagnosis for the problem of Chikungunya disease using soft rough sets
One of the most difficulties that doctors face when diagnosing a disease is making an
accurate decision to correctly determine the nature of the injury. This is attributable to the …
accurate decision to correctly determine the nature of the injury. This is attributable to the …
Data classification using rough set and bioinspired computing in healthcare applications-an extensive review
The change in living standard made people to think on their physical health. Accordingly,
healthcare organizations are concentrating more on physical health of people in terms of …
healthcare organizations are concentrating more on physical health of people in terms of …
Ischemic heart disease multiple imputation technique using machine learning algorithm
Medical data sets in profound data repository like the University of California Irvin (UCI) has
missing values. These essential data are used for multiple analyses by researchers in a …
missing values. These essential data are used for multiple analyses by researchers in a …