Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …
applications in healthcare, such as health services management, predictive medicine …
Real-world data: a brief review of the methods, applications, challenges and opportunities
F Liu, D Panagiotakos - BMC Medical Research Methodology, 2022 - Springer
Background The increased adoption of the internet, social media, wearable devices, e-
health services, and other technology-driven services in medicine and healthcare has led to …
health services, and other technology-driven services in medicine and healthcare has led to …
Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
Human postprandial responses to food and potential for precision nutrition
Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-
resolution studies are lacking. We recruited n= 1,002 twins and unrelated healthy adults in …
resolution studies are lacking. We recruited n= 1,002 twins and unrelated healthy adults in …
[HTML][HTML] An overview of deep learning in medical imaging focusing on MRI
AS Lundervold, A Lundervold - Zeitschrift für Medizinische Physik, 2019 - Elsevier
What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
[HTML][HTML] Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
The identification of landslide-prone areas is an essential step in landslide hazard
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
assessment and mitigation of landslide-related losses. In this study, we applied two novel …
[HTML][HTML] Literature review: Efficient deep neural networks techniques for medical image analysis
MA Abdou - Neural Computing and Applications, 2022 - Springer
Significant evolution in deep learning took place in 2010, when software developers started
using graphical processing units for general-purpose applications. From that date, the deep …
using graphical processing units for general-purpose applications. From that date, the deep …
[HTML][HTML] Deep learning in medical image registration: a survey
The establishment of image correspondence through robust image registration is critical to
many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring …
many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring …
Artificial intelligence in radiology
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated
remarkable progress in image-recognition tasks. Methods ranging from convolutional neural …
remarkable progress in image-recognition tasks. Methods ranging from convolutional neural …
Artificial intelligence in drug development: present status and future prospects
KK Mak, MR Pichika - Drug discovery today, 2019 - Elsevier
Highlights•Advances in artificial intelligence (AI) are modernising several aspects of our
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …