Leveraging big data analytics in healthcare enhancement: trends, challenges and opportunities

A Rehman, S Naz, I Razzak - Multimedia Systems, 2022 - Springer
Clinical decisions are more promising and evidence-based, hence, big data analytics to
assist clinical decision-making has been expressed for a variety of clinical fields. Due to the …

Application of deep learning models for automated identification of Parkinson's disease: A review (2011–2021)

HW Loh, W Hong, CP Ooi, S Chakraborty, PD Barua… - Sensors, 2021 - mdpi.com
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting
over 6 million people globally. Although there are symptomatic treatments that can increase …

Employing deep learning and transfer learning for accurate brain tumor detection

SK Mathivanan, S Sonaimuthu, S Murugesan… - Scientific Reports, 2024 - nature.com
Artificial intelligence-powered deep learning methods are being used to diagnose brain
tumors with high accuracy, owing to their ability to process large amounts of data. Magnetic …

A deep learning-based framework for automatic brain tumors classification using transfer learning

A Rehman, S Naz, MI Razzak, F Akram… - Circuits, Systems, and …, 2020 - Springer
Brain tumors are the most destructive disease, leading to a very short life expectancy in their
highest grade. The misdiagnosis of brain tumors will result in wrong medical intercession …

A deep learning model based on concatenation approach for the diagnosis of brain tumor

N Noreen, S Palaniappan, A Qayyum, I Ahmad… - IEEE …, 2020 - ieeexplore.ieee.org
Brain tumor is a deadly disease and its classification is a challenging task for radiologists
because of the heterogeneous nature of the tumor cells. Recently, computer-aided …

[HTML][HTML] An effective approach to detect and identify brain tumors using transfer learning

N Ullah, JA Khan, MS Khan, W Khan, I Hassan… - Applied Sciences, 2022 - mdpi.com
Brain tumors are considered one of the most serious, prominent and life-threatening
diseases globally. Brain tumors cause thousands of deaths every year around the globe …

Efficient deep learning approach for augmented detection of Coronavirus disease

A Sedik, M Hammad, FE Abd El-Samie… - Neural Computing and …, 2022 - Springer
The new Coronavirus disease 2019 (COVID-19) is rapidly affecting the world population
with statistics quickly falling out of date. Due to the limited availability of annotated …

Big data analytics for preventive medicine

MI Razzak, M Imran, G Xu - Neural Computing and Applications, 2020 - Springer
Medical data is one of the most rewarding and yet most complicated data to analyze. How
can healthcare providers use modern data analytics tools and technologies to analyze and …

Robust automated Parkinson disease detection based on voice signals with transfer learning

O Karaman, H Çakın, A Alhudhaif, K Polat - Expert Systems with …, 2021 - Elsevier
Parkinson's disease (PD) is a progressive-neurodegenerative disorder that affects more
than 6 million people around the world. However, conventional techniques for PD detection …

Effectiveness of federated learning and CNN ensemble architectures for identifying brain tumors using MRI images

M Islam, MT Reza, M Kaosar, MZ Parvez - Neural Processing Letters, 2023 - Springer
Medical institutions often revoke data access due to the privacy concern of patients.
Federated Learning (FL) is a collaborative learning paradigm that can generate an unbiased …