查看更多>>摘要：In patients with major depression disorder it is, thanks to use of artificial intelligence, now possible to predict within a week whether an antidepressant will work. With the help of an AI algorithm, a brain scan and an individual’s clinical information, researchers from Amsterdam UMC and Radboudumc could see up to 8 weeks faster whether or not the medication would work. The results of this study are published in the American Journal of Psychiatry.
查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating in Brussels, Belgium, by NewsRx journalists, research stated, “The development of skeletal mechanisms has become essential for multi-dimensional simulations of plasma-assisted combustion (PAC). However, reduction tools developed for traditional combustion applications are not always applicable to PAC, due to the complex interplay between non-equilibrium plasma and combustion kinetics.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating from Sichuan, People’s Republic of China, by NewsRx correspondents, research stated, “Cholangiocarcinoma (CCA) is a highly aggressive hepatobiliary malignancy, second only to hepatocellular carcinoma in prevalence. Despite surgical treatment being the recommended method to achieve a cure, it is not viable for patients with advanced CCA.”
查看更多>>摘要：New research on Vascular Diseases and Conditions - Ischemia is the subject of a report. According to news reporting originating in Ottawa, Canada, by NewsRx journalists, research stated, “Quantification of myocardial blood flow (MBF) is used for the noninvasive diagnosis of patients with coronary artery disease (CAD). This study compared traditional statistics, machine learning, and deep learning techniques in their ability to diagnose disease using only the rest and stress MBF values.”
查看更多>>摘要：Investigators publish new report on robotics. According to news reporting from Xian Jiao Tong University by NewsRx journalists, research stated, “With the continuous development of the manufacturing industry, the application of intelligent robots is becoming more and more extensive.” Our news editors obtained a quote from the research from Xian Jiao Tong University: “Many emerging technologies can be applied to intelligent robots. Typical intelligent robots still have room for further improvement in terms of automatic control and adaptation to the surrounding environment. And independent learning of production tasks and realization of human-computer interaction is the future development direction of industrial robots. In view of these deficiencies, the development of intelligent robots is particularly important. This paper introduces the application fields, key technologies and needs of intelligent robots, and explains the important position of intelligent robots in the future manufacturing industry.”
查看更多>>摘要：Current study results on artificial intelligence have been published. According to news reporting originating from Guangdong, People’s Republic of China, by NewsRx correspondents, research stated, “It appears from the information that Character recognition research is currently focused on handwritten digit recognition, a significant subfield of optical character recognition, i.e. the use of computers to recognise and process digital information.”
查看更多>>摘要：A new study on Robotics is now available. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “To steer a soft robot precisely in an unconstructed environment with minimal collision remains an open challenge for soft robots. When the environments are unknown, prior motion planning for navigation may not always be available.”
查看更多>>摘要：A new study on artificial intelligence is now available. According to news originating from Xuzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Nowadays, the world is still in the environment of economic depression.” Our news correspondents obtained a quote from the research from Jiangsu Normal University: “In order to promote economic recovery, improve Relations of production and production efficiency, stimulate consumption expansion and upgrading, and accelerate industrial transformation and upgrading, problems such as industrial upgrading need to be solved urgently. Solving the above problems requires more useful tools, and artificial intelligence is one of them. Machine learning is the key to distinguishing artificial intelligence from ordinary program code. Unlike people learning knowledge, machine learning has its own unique language algorithms and behavioral logic. Machine learning, as a technology active in the field of artificial intelligence in recent years, specializes in studying how computers learn, simulate and realize part of human learning behavior, so as to provide data mining and behavior prediction for humans, to obtain new knowledge or skills, or to strengthen the original basic ability of machines.”
查看更多>>摘要：Investigators publish new report on Nanotechnology - Nanoparticles. According to news originating from Campinas, Brazil, by NewsRx correspondents, research stated, “Mono- and multimetallic nanoparticles have been extensively studied in various fields due to their tunable physicochemical properties and potential for replacing expensive metals with more abundant and affordable ones. The chemical structure, i.e., the spatial distribution of elements inside nanoparticles, plays a crucial role in defining their properties, particularly in catalytic processes.”
查看更多>>摘要：Researchers detail new data in . According to news originating from Barranquilla, Colombia, by NewsRx correspondents, research stated, “Graphs classification is a relevant problem that arises in many disciplines.” The news editors obtained a quote from the research from University of the North: “Using graphs directly instead of vectorization allows exploiting the intrinsic representations of the data. Support Vector Machines (SVM) is a supervised learning method based on the use of graph kernel functions used for this task. One of the problems of SVM, as the number of samples increases, is the cost of storing and solving the optimization problem related to SVM. In this work, we propose a method capable of finding a small representative subset of the whole graph data set such that an approximate solution of the SVM optimization problem can be obtained in a fraction of the time, and without significantly degrading the classification prediction error. The method is based on the use of Locality-Sensitive Hashing for projecting over the Hilbert spaces defined by appropriate graph kernels that measure similarity between the graphs. A description of the algorithm, as well as numerical results using two graph kernels (Simple Product and Random Walk) on simulated and real life data sets are presented.”
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