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Artificial Intelligence Market Fintech Forecast 2017 2022 PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest Artificial Intelligence Market Fintech Forecast 2017 2022 articles that have been published worldwide.
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This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-...
Market timing is an investment technique that tries to continuously switch investment into assets forecast to have better returns. What is the likelihood of having a successful market timing strategy? With an emphasis on modeling simplicity, I calculate the feasible set of market timing portfolios using index mutual fund data for perfectly timed (by hindsight) all or nothing quarterly switching between two asset classes, US stocks and bonds over the time period 1993-2017. The historical optimal timing path ...
To assess undergraduate medical students' attitudes towards artificial intelligence (AI) in radiology and medicine.
Despite decades-long reductions in cardiovascular disease (CVD) mortality, CVD mortality rates have recently plateaued and even increased in some subgroups, and the prevalence of CVD risk factors remains high. Million Hearts 2022, a 5-year initiative, was launched in 2017 to address this burden. This report establishes a baseline for the CVD risk factors targeted for reduction by the initiative during 2017-2021 and highlights recent changes over time.
Artificial Intelligence (AI) is a branch of computer science that deals with the development of algorithms that seek to simulate human intelligence. We provide an overview of the basic principles in AI that are essential to the understanding of AI and its application to health care. We also present a descriptive analysis of the current state of AI in various fields of medicine, especially ophthalmology. Finally, we review the potential limitations and challenges that come along with the development and impl...
The evaluation of Acne using ordinal scales reflects the clinical perception of severity but has shown low reproducibility both intra- and inter-rater. In this study, we investigated if Artificial Intelligence trained on images of Acne patients could perform acne grading with high accuracy and reliabilities superior to those of expert physicians.
The prognosis of esophageal cancer is relatively poor. Patients are usually diagnosed at an advanced stage when it is often too late for effective treatment. Recently, artificial intelligence (AI) using deep learning has made remarkable progress in medicine. However, there are no reports on its application for diagnosing esophageal cancer. Here, we demonstrate the diagnostic ability of AI to detect esophageal cancer including squamous cell carcinoma and adenocarcinoma.
A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language.
Despite its preventability, cardiovascular disease remains a leading cause of morbidity, mortality, and health care costs in the United States. This study describes the burden, in 2016, of nonfatal and fatal cardiovascular events targeted for prevention by Million Hearts 2022, a national initiative working to prevent one million cardiovascular events during 2017-2021.
The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection.
To select, present, and summarize the best papers published in 2017 in the field of Knowledge Representation and Management (KRM).
An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and yet 1 in 2 persons remain undiagnosed and untreated. Applications of artificial intelligence (AI) and cognitive computing offer promise in diabetes care. The purpose of this article is to better understand what AI advances may be relevant today to persons with diabetes (PWDs), their clinicians, family, and caregivers. The authors conducted a predefined, online PubMed search of publicly availabl...
Digitalization is transforming every aspect of life, it is also transforming deeply medicine. The digitalization era is characterized by a large production of new data streams while existing processes are progressively migrated, such as writing or imaging. The very large and fast-growing amount of data available requires new storage, transport and analytical tools. This paper presents some of them, such as natural language processing, artificial intelligence, and graph databases. A short introduction to the...
Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hypertension and applying them to personalized management. This review summarizes recent advances in the computer science and medical field, illustrating the innovative AI approach for potential prediction of early stages of hypertension. Additionally, we review ongoing research and futu...
Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of system...
The profit of greenhouse production is influenced by management activities (e.g., environmental control and plantation scheduling) as well as social conditions (e.g., price fluctuation). In China, the prevailing horticultural facility is the traditional solar greenhouse. The key existing problem is the lack of knowledge of growers, which in turn leads to inefficient management, low production, or unsalable products. To secure effective greenhouse management, the production planning system must account for t...
Recently, deep learning has been advancing the state of the art in artificial intelligence to a new level, and humans rely on artificial intelligence techniques more than ever. However, even with such unprecedented advancements, the lack of explanation regarding the decisions made by deep learning models and absence of control over their internal processes act as major drawbacks in critical decision-making processes, such as precision medicine and law enforcement. In response, efforts are being made to make...
The objective of this study was to identify the extent to which artificial intelligence could be used in the diagnosis of Parkinson's disease from ioflupane-123 (I) single-photon emission computed tomography (SPECT) dopamine transporter scans using transfer learning.