Latest AI and machine learning research in cultural competence for healthcare professionals.
Previous studies have demonstrated the feasibility of reducing noise with deep learning-based methods for low-dose fluorodeoxyglucose (FDG) positron emission tomography (PET). This work aimed to investigate the feasibility of noise reduction for tracers without sufficient training datasets using a deep transfer learning approach, which can utilize existing networks trained by the widely available ...
The ubiquity of social media usage has led to exciting new technologies such as machine learning. Machine learning is poised to change many fields of health, including psychology. The wealth of information provided by each social media user in combination with machine learning technologies may pave the way for automated psychological assessment and diagnosis. Assessment of individuals' social medi...
Tropical biomes are the most diverse plant communities on Earth, and quantifying this diversity at large spatial scales is vital for many purposes. As...
Most real-world networks are incompletely observed. Algorithms that can accurately predict which links are missing can dramatically speed up network d...
Nucleic acids exhibit a repertoire of conformational preference depending on the sequence and environment. Circular dichroism (CD) is an essential and...
Traditionally, machine learning algorithms relied on reliable labels from experts to build predictions. More recently however, algorithms have been re...
Occurrence of the smallest phototrophic microorganisms (photoautotrophic picoplankton, APP) in Lake Balaton was discovered in the early 1980s. This tr...
The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and acc...
Deep generative models seek to recover the process with which the observed data was generated. They may be used to synthesize new samples or to subseq...
Machine learning methods have been employed to make predictions in psychiatry from genotypes, with the potential to bring improved prediction of outco...
Engineering gene and protein sequences with defined functional properties is a major goal of synthetic biology. Deep neural network models, together w...
In many objective optimization problems (MaOPs), more than three distinct objectives are optimized. The challenging part in MaOPs is to get the Pareto...
Advances in the application of artificial intelligence, digitization, technology, iCloud computing, and wearable devices in health care predict an exc...
The efficiency of disease prevention and medical care service necessitated the prediction of incidence. However, predictive accuracy and power were la...
PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain PET scanners and hybrid PET/MRI, is challenging. ...
Allowing machines to choose whether to kill humans would be devastating for world peace and security. But how do we equip machines with the ability to...
Accurate assessment of renal function is essential in hospitalized elderly patients. Few studies have examined the accuracy of Cockcroft-Gault (C-G) ...
Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due...
Artificial intelligence (AI) assisted human brain research is a dynamic interdisciplinary field with great interest, rich literature, and huge diversi...
The objective of this article is to discuss the inherent bias involved with artificial intelligence-based decision support systems for healthcare. In ...