Studies in health technology and informatics
Jun 29, 2022
This study aimed at testing the feasibility of neurosurgical procedures classification into 100+ classes using natural language processing and machine learning. A catboost algorithm and bidirectional recurrent neural network with a gated recurrent un...
Studies in health technology and informatics
Jun 29, 2022
Most screening tests for Diabetes Mellitus (DM) in use today were developed using electronically collected data from Electronic Health Record (EHR). However, developing and under-developing countries are still struggling to build EHR in their hospita...
Studies in health technology and informatics
Jun 29, 2022
Artificial Intelligence (AI) has made major progress in recent years in many fields. With regard of medicine however, the utilization of AI raises numerous ethical questions, especially since newer and much more accurate algorithms function as black ...
Studies in health technology and informatics
Jun 29, 2022
Static and dynamic gestures are frequently used in activities supporting learning, recovery healthcare, engineering, and 3D games to increase the interactivity between man and machine. The gestures are detected via hardware devices and data is proces...
Studies in health technology and informatics
Jun 29, 2022
Brain Imaging Data Structure (BIDS) provides a valuable tool to organise brain imaging data into a clear and easy standard directory structure. Moreover, BIDS is widely supported by the scientific community and has been established as a powerful stan...
MOTIVATION: Automated molecule generation is a crucial step in in-silico drug discovery. Graph-based generation algorithms have seen significant progress over recent years. However, they are often complex to implement, hard to train and can under-per...
MOTIVATION: The emergence of next-generation sequencing techniques opens up tremendous opportunities for researchers to uncover the basic mechanisms of disease at the molecular level. Recently, automatic machine learning (AutoML) frameworks have been...
OBJECTIVES: To reduce the dimension of characteristic information extracted from pelvic CT images by using principal component analysis (PCA) and partial least squares (PLS) methods. To establish a support vector machine (SVM) classification and iden...
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