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[HTML][HTML] Unraveling the ethical enigma: artificial intelligence in healthcare
M Jeyaraman, S Balaji, N Jeyaraman, S Yadav - Cureus, 2023 - ncbi.nlm.nih.gov
The integration of artificial intelligence (AI) into healthcare promises groundbreaking
advancements in patient care, revolutionizing clinical diagnosis, predictive medicine, and …
advancements in patient care, revolutionizing clinical diagnosis, predictive medicine, and …
Exploring the intersection of artificial intelligence and clinical healthcare: a multidisciplinary review
Artificial intelligence (AI) plays a more and more important role in our everyday life due to the
advantages that it brings when used, such as 24/7 availability, a very low percentage of …
advantages that it brings when used, such as 24/7 availability, a very low percentage of …
Revolutionizing spinal care: Current applications and future directions of artificial intelligence and machine learning
M Yagi, K Yamanouchi, N Fujita, H Funao… - Journal of Clinical …, 2023 - mdpi.com
Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral
components of modern healthcare, offering new avenues for diagnosis, treatment, and …
components of modern healthcare, offering new avenues for diagnosis, treatment, and …
[HTML][HTML] Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities
In recent years, machine learning (ML) and deep learning (DL) have been the leading
approaches to solving various challenges, such as disease predictions, drug discovery …
approaches to solving various challenges, such as disease predictions, drug discovery …
Unscramble social media power for waste management: A multilayer deep learning approach
Abstract In an industry 4.0 era, manufacturers must make the right decisions concerning
reutilizing and recycling returned goods to lower waste by connecting and integrating …
reutilizing and recycling returned goods to lower waste by connecting and integrating …
A hybrid machine learning approach to screen optimal predictors for the classification of primary breast tumors from gene expression microarray data
The high dimensionality and sparsity of the microarray gene expression data make it
challenging to analyze and screen the optimal subset of genes as predictors of breast …
challenging to analyze and screen the optimal subset of genes as predictors of breast …
[HTML][HTML] Early diagnosis and personalised treatment focusing on synthetic data modelling: novel visual learning approach in healthcare
The early diagnosis and personalised treatment of diseases are facilitated by machine
learning. The quality of data has an impact on diagnosis because medical data are usually …
learning. The quality of data has an impact on diagnosis because medical data are usually …
Performance of artificial intelligence-based algorithms to predict prolonged length of stay after lumbar decompression surgery
Background: Decompression of the lumbar spine is one of the most common procedures
performed in spine surgery. Hospital length of stay (LOS) is a clinically relevant metric used …
performed in spine surgery. Hospital length of stay (LOS) is a clinically relevant metric used …
Associations between periodontitis and COPD: an artificial intelligence-based analysis of NHANES III
A Vollmer, M Vollmer, G Lang, A Straub… - Journal of clinical …, 2022 - mdpi.com
A number of cross-sectional epidemiological studies suggest that poor oral health is
associated with respiratory diseases. However, the number of cases within the studies was …
associated with respiratory diseases. However, the number of cases within the studies was …
Current and emerging approaches for spine tumor treatment
Spine tumors represent a significant social and medical problem, affecting the quality of life
of thousands of patients and imposing a burden on healthcare systems worldwide …
of thousands of patients and imposing a burden on healthcare systems worldwide …