Current uses, emerging applications, and clinical integration of artificial intelligence in neuroradiology

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Brian Fiani ◽  
Kory B. Dylan Pasko ◽  
Kasra Sarhadi ◽  
Claudia Covarrubias
Keyword(s):  
Artificial Intelligence ◽  
Healthcare Delivery ◽  
Data Interpretation ◽  
Medical Data ◽  
Human Cognition ◽  
Scientific Validity ◽  
Clinical Integration ◽  
Management Diagnostics ◽  
Accurate Imaging

Abstract Artificial intelligence (AI) is a branch of computer science with a variety of subfields and techniques, exploited to serve as a deductive tool that performs tasks originally requiring human cognition. AI tools and its subdomains are being incorporated into healthcare delivery for the improvement of medical data interpretation encompassing clinical management, diagnostics, and prognostic outcomes. In the field of neuroradiology, AI manifested through deep machine learning and connected neural networks (CNNs) has demonstrated incredible accuracy in identifying pathology and aiding in diagnosis and prognostication in several areas of neurology and neurosurgery. In this literature review, we survey the available clinical data highlighting the utilization of AI in the field of neuroradiology across multiple neurological and neurosurgical subspecialties. In addition, we discuss the emerging role of AI in neuroradiology, its strengths and limitations, as well as future needs in strengthening its role in clinical practice. Our review evaluated data across several subspecialties of neurology and neurosurgery including vascular neurology, spinal pathology, traumatic brain injury (TBI), neuro-oncology, multiple sclerosis, Alzheimer’s disease, and epilepsy. AI has established a strong presence within the realm of neuroradiology as a successful and largely supportive technology aiding in the interpretation, diagnosis, and even prognostication of various pathologies. More research is warranted to establish its full scientific validity and determine its maximum potential to aid in optimizing and providing the most accurate imaging interpretation.

scholarly journals ASSESSING THE ROLE OF ARTIFICIAL INTELLIGENCE IN THE DESIGN OF DRUG DELIVERY SYSTEMS

2020 ◽  
Vol 4 (12) ◽  
Author(s):  
Abdul Waheed ◽  
Ashwin K ◽  
Hima Bindu M
Keyword(s):  
Artificial Intelligence ◽  
Drug Delivery ◽  
Data Interpretation ◽  
Transport Systems ◽  
Diagnostic Strategies ◽  
Drug Candidates ◽  
Speed Up ◽  
Small Molecule Modulator ◽  
Target Fishing

Over ten years, increasing the interest has been fascinated towards the appeal of intelligent retrieval (IR) technology for data interpretation and illuminate the biological or transmitted information, speed up drug invention, and pinpointing of the selective small-molecule modulator control or rare particle and projection of their behavior. To make use of biomaterials, synthetic resin, fats, along IR is upcoming for the manufacture of drug deliverables. The request of the computerized workflows and databases for quick calculation of the vast amounts of data and artificial neural networks (ANNs) for growth of the narrative proposition and treatment schemes, forecast of disease development, and judgment of the pharmacological description of drug candidates may consequently improve treatment outcomes. Target fishing (TG) by quick projection or identification of the biological quarry might be of great help for linking quarry to the new substance.AI and TF methods in union with human knowledge may indeed transform the present-day diagnostic strategies, meanwhile verifying approaches are necessary to overcome the possible challenges and make certain higher perfection. In this review, the importance of AI and TF in the growth of drugs and transport systems and the possible challenging topics have been spotlighted. Keywords: Artificial intelligence; biomaterials, polymers, lipids, Drug Delivery.

scholarly journals Requirement of artificial intelligence technology awareness for thoracic surgeons

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Anshuman Darbari ◽  
Krishan Kumar ◽  
Shubhankar Darbari ◽  
Prashant L. Patil
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Robots ◽  
Healthcare Delivery ◽  
Data Interpretation ◽  
Review Article ◽  
Physiological Data ◽  
Main Body ◽  
Thoracic Imaging ◽  
Thoracic Surgical Procedures ◽  
Artificial Intelligence Technology

Abstract Background We have recently witnessed incredible interest in computer-based, internet web-dependent mechanisms and artificial intelligence (AI)-dependent technique emergence in our day-to-day lives. In the recent era of COVID-19 pandemic, this nonhuman, machine-based technology has gained a lot of momentum. Main body of the abstract The supercomputers and robotics with AI technology have shown the potential to equal or even surpass human experts’ accuracy in some tasks in the future. Artificial intelligence (AI) is prompting massive data interweaving with elements from many digital sources such as medical imaging sorting, electronic health records, and transforming healthcare delivery. But in thoracic surgical and our counterpart pulmonary medical field, AI’s main applications are still for interpretation of thoracic imaging, lung histopathological slide evaluation, physiological data interpretation, and biosignal testing only. The query arises whether AI-enabled technology-based or autonomous robots could ever do or provide better thoracic surgical procedures than current surgeons but it seems like an impossibility now. Short conclusion This review article aims to provide information pertinent to the use of AI to thoracic surgical specialists. In this review article, we described AI and related terminologies, current utilisation, challenges, potential, and current need for awareness of this technology.

The Role of Numeracy and Intelligence in Health-Risk Estimation and Medical Data Interpretation

2013 ◽  
Vol 27 (2) ◽  
pp. 95-108 ◽  
Author(s):  
Torstein Låg ◽  
Lars Bauger ◽  
Martin Lindberg ◽  
Oddgeir Friborg
Keyword(s):  
Health Risk ◽  
Risk Estimation ◽  
Data Interpretation ◽  
Medical Data ◽  
Health Risk Estimation

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

Quantitative Conditions and Convergent Operations That Are Compatible With the Universe as a Persistent Generator of Successive Simulations

2016 ◽  
Vol 12 (1) ◽  
pp. 4178-4187
Author(s):  
Michael A Persinger ◽  
Stanley A Koren
Keyword(s):  
Structural Organization ◽  
Total Duration ◽  
Human Cognition ◽  
Intrinsic Properties ◽  
Basic Assumptions ◽  
Electron Orbit ◽  
Quantitative Analyses ◽  
Massive Information ◽  
The Universe

                The capacity for computer-like simulations to be generated by massive information processing from electron-spin potentials supports Bostrom’s hypothesis that matter and human cognition might reflect simulations. Quantitative analyses of the basic assumptions indicate the universe may display properties of a simulation where photons behave as pixels and gravitons control the structural organization. The Lorentz solution for the square of the light and entanglement velocities converges with the duration of a single electron orbit that ultimately defines properties of matter. The approximately one trillion potential states within the same space with respect to the final epoch of the universe indicate that a different simulation, each with intrinsic properties, has been and will be generated as a type of tractrix defined by ±2 to 3 days (total duration 5 to 6 days). It may define the causal limits within a simulation. Because of the intrinsic role of photons as the pixel unit, phenomena within which flux densities are enhanced, such as human cognition (particularly dreaming) and the cerebral regions associated with those functions, create the conditions for entanglement or excess correlations between contiguous simulations. The consistent quantitative convergence of operations indicates potential validity for this approach. The emergent solutions offer alternative explanations for the limits of predictions for multivariate phenomena that could be coupled to more distal simulations.

Artificial intelligence and the management transformation

2020 ◽  
Vol 16 (4) ◽  
pp. 600-612
Author(s):  
L.F. Nikulin ◽  
V.V. Velikorossov ◽  
S.A. Filin ◽  
A.B. Lanchakov
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Soft Power ◽  
Process Integration ◽  
Management Practice ◽  
Scientific School ◽  
Strategic Culture ◽  
Analysis And Synthesis ◽  
And Training

Subject. The article discusses how management transforms as artificial intelligence gets more important in governance, production and social life. Objectives. We identify and substantiate trends in management transformation as artificial intelligence evolves and gets more important in governance, production and social life. The article also provides our suggestions for management and training of managers dealing with artificial intelligence. Methods. The study employs methods of logic research, analysis and synthesis through the systems and creative approach, methodology of technological waves. Results. We analyzed the scope of management as is and found that threats and global challenges escalate due to the advent of artificial intelligence. We provide the rationale for recognizing the strategic culture as the self-organizing system of business process integration. We suggest and substantiate the concept of soft power with reference to strategic culture, which should be raised, inter alia, through the scientific school of conflict studies. We give our recommendations on how management and training of managers should be improved in dealing with artificial intelligence as it evolves. The novelty hereof is that we trace trends in management transformation as the role of artificial intelligence evolves and growth in governance, production and social life. Conclusions and Relevance. Generic solutions are not very effective for the Russian management practice during the transition to the sixth and seventh waves of innovation. Any programming product represents artificial intelligence, which simulates a personality very well, though unable to substitute a manager in motivating, governing and interacting with people.

The Role of Theories of Embodied Cognition in Research and Modeling of Emotions

2019 ◽  
Vol 62 (5) ◽  
pp. 124-138
Author(s):  
Alexandra V. Shiller
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Mirror Neurons ◽  
Empirical Studies ◽  
Unknown Quantity ◽  
Emotional Processes ◽  
Strong Artificial Intelligence ◽  
European Philosophy ◽  
Postmodern Philosophy

The article analyzes the role of theories of embodied cognition for the development of emotion research. The role and position of emotions changed as philosophy developed. In classical and modern European philosophy, the idea of the “primacy of reason” prevailed over emotions and physicality, emotions and affective life were described as low-ranking phenomena regarding cognitive processes or were completely eliminated as an unknown quantity. In postmodern philosophy, attention focuses on physicality and sensuality, which are rated higher than rational principle, mind and intelligence. Within the framework of this approach, there is a recently emerged theory of embodied cognition, which allows to take a fresh look at the place of emotions in the architecture of mental processes – thinking, perception, memory, imagination, speech. The article describes and analyzes a number of empirical studies showing the impossibility of excluding emotional processes and the significance of their research for understanding the architecture of embodied cognition. However, the features of the architecture of embodied cognition remain unclear, and some of the discoveries of recent years (mirror neurons or neurons of simulation) rather raise new questions and require further research. The rigorously described and clear architecture of the embodied cognition can grow the theoretical basis that will allow to advance the studies of learning processes, language understanding, psychotherapy techniques, social attitudes and stereotypes, highlight the riddle of consciousness and create new theories of consciousness or even create an anthropomorphic artificial intelligence that is close to “strong artificial intelligence.”

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