scholarly journals Current and Future Photography Techniques in Aesthetic Surgery

2021 ◽  
Author(s):  
Shyon Parsa ◽  
Berkay Basagaoglu ◽  
Kate Mackley ◽  
Patricia Aitson ◽  
Jeffrey Kenkel ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Aesthetic Surgery ◽  
Current Data ◽  
Outcome Expectation ◽  
Image Capture ◽  
Clinical Photography ◽  
Operative Outcomes ◽  
Viewing Screen ◽  
Patient Service ◽  
2D And 3D

Abstract Background The rapidly increasing modalities and mediums of clinical photography, use of 3D and 4D patient modeling, and widening implementation of cloud-based storage and artificial intelligence call for an overview of various methods currently in use as well as future considerations in the field. Objectives Through a close look at the methods used in aesthetic surgery photography, clinicians will be able to select the modality best suited to their practice and goals. Methods Review and discussion of current data pertaining to: 2D and 3D clinical photography, current photography software, augmented reality reconstruction, artificial intelligence photography, and cloud-based storage. Results Important considerations for current image capture include a device with a gridded viewing screen and high megapixel resolution, a tripod with leveling base, studio lighting with dual-sourced light, standardized matte finish background, and consistency in patient orientation. Currently, 3D and 4D photography devices offer advantages such as improved communication to the patient on outcome expectation and better quality of patient service and safety. Artificial intelligence may contribute to post-capture processing and 3D printing of post-operative outcomes. Current smartphones distort patient perceptions about their appearance and should be used cautiously in an aesthetic surgery setting. Cloud-based storage provides flexibility, cost, and ease of service while remaining vulnerable to data breaches. Conclusions While there are advancements to be made in the physical equipment and preparation for the photograph, the future of clinical photography will be heavily influenced by innovations in software and 3D and 4D modeling of outcomes.

scholarly journals A Practical Approach to Artificial Intelligence in Plastic Surgery

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Akash Chandawarkar ◽  
Christian Chartier ◽  
Jonathan Kanevsky ◽  
Phaedra E Cress
Keyword(s):  
Artificial Intelligence ◽  
Data Collection ◽  
Plastic Surgery ◽  
Aesthetic Surgery ◽  
Practical Approach ◽  
Quality Data ◽  
Surgical Innovation ◽  
Mathematical Basis ◽  
New Era ◽  
Quantitative Studies

Abstract Understanding the intersection of technology and plastic surgery has been and will be essential to positioning plastic surgeons at the forefront of surgical innovation. This account of the current and future applications of artificial intelligence (AI) in reconstructive and aesthetic surgery introduces us to the subset of issues amenable to support from this technology. It equips plastic surgeons with the knowledge to navigate technical conversations with peers, trainees, patients, and technical partners for collaboration and to usher in a new era of technology in plastic surgery. From the mathematical basis of AI to its commercially viable applications, topics introduced herein constitute a framework for design and execution of quantitative studies that will better outcomes and benefit patients. Finally, adherence to the principles of quality data collection will leverage and amplify plastic surgeons’ creativity and undoubtedly drive the field forward.

scholarly journals A Training Gesture-Based-Scroll Visual Artificial Intelligence And Measuring Its Effectiveness Using Hidden-Markov Modeling Methods

2020 ◽  
Vol 2 (1) ◽  
pp. 163-168
Author(s):  
Arif Wibisono
Keyword(s):  
Artificial Intelligence ◽  
Gesture Recognition ◽  
Motion Detection ◽  
Visual Motion ◽  
Hidden Markov ◽  
Hand Gesture ◽  
Markov Modeling ◽  
Image Capture ◽  
Modeling Methods ◽  
Hidden Markov Modeling

In this article I discuss the method of hand gesture recognition as a visual motion detection based on artificial intelligence by training three main movements namely, scrolling up, scrolling down and stopping based on capturing the front camera image capture speed of 3 fps and measuring its efficiency against the control movements that performed using Hidden-Markov Modeling (HMM) with each catch object scroll up 3 fps / 15 frames scroll down scroll down 3 fps / 15 frames and stop 3 fps / 9 frames, the result is that the most effective hand gesture object training movement is stop gesture with 3 fps / 9 frames because the object's movement is able to be recognized by the system only in the 3rd second image capture frame.

Analysis of regression prediction model of competitive sports based on SVM and artificial intelligence

2020 ◽  
Vol 39 (4) ◽  
pp. 5859-5869
Author(s):  
Jun Wang ◽  
Hongjun Qu
Keyword(s):  
Artificial Intelligence ◽  
Prediction Model ◽  
Optimization Method ◽  
Kernel Functions ◽  
Support Vector ◽  
Competitive Sports ◽  
Statistical Efficiency ◽  
Image Capture ◽  
Rbf Kernel ◽  
Speed Prediction

The training effect is not only affected by many environmental disturbance factors, but also related to various factors such as the athlete itself. In this paper, the author analyze the regression prediction model of competitive sports based on SVM and artificial intelligence. Traditional statistical modeling simply compares existing data between players and compares them between data. Moreover, it is unable to formulate corresponding tactical strategies according to the situation of the opponent, and targeted training to strengthen the level of individual sports skills.By com-paring the effects of several kernel functions on the SVM modeling side, it is found that the RBF kernel function can make the SVM’s prediction performance the best when dealing with the speed prediction problem. The experimental results show that this parameter optimization method can significantly improve the performance of the SVM regression machine. The prediction model based on support vector machine can effectively improve the prediction direction. Using artificial intelligence and image capture technology in sports can effectively improve the statistical efficiency and prediction effect of competition.

Camera Systems of Industrial Robots

2016 ◽  
Vol 844 ◽  
pp. 68-74 ◽  
Author(s):  
Vladimír Baláž ◽  
Marek Vagaš ◽  
Ján Semjon ◽  
Rudolf Rusnák
Keyword(s):  
Image Processing ◽  
Industrial Robots ◽  
Image Capture ◽  
Camera Systems ◽  
3D Camera ◽  
2D And 3D

The article deals with problems of image capture. There are presented methods of image processing through 2D and 3D camera systems. Section dedicated to image processing refers to the possibility of using different filters images, geometric and brightness transformations.

scholarly journals UTILIZATION OF ARTIFICIAL INTELLIGENCE IN PUBLIC RELATIONS AS A BOUNDARY SPANNING IN E-COMMERCE TYPE OF B2C

2018 ◽  
Vol 19 (1) ◽  
pp. 4-17
Author(s):  
Marsheila Gloria
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Public Relations ◽  
Boundary Spanning ◽  
Current Data ◽  
Corporate Communications ◽  
Online Sales ◽  
Processing Information ◽  
The Right

Business competition in website-based online sales in the shape of e-commerce in Indonesia creates a challenge for e-commerce companies to have the right strategy to increase the customers’ interest so that they will make a purchase transaction through the e-commerce. As one of e-commerce with Busines to Customer (B2C) transactions, Sale Stock (www.salestockindonesia.com) applies the role of public relations as boundary spanning as a strategy to manage corporate communications with customers. The application of this public relations role is carried out by utilizing Artificial Intelligence (AI) named Soraya as a liaison or provider of information formalized through the Information Technology (IT) channel, scanning and monitoring the organization's external environment, protecting organizations, processing information coming from outside the organization, and gathering, channeling, and selecting current data flows and then becoming information analysis. For Sale Stock, utilizing communication and information technology in the role of public relations will bring benefits in the form of ease of companies to communicate with new customers, promote products to new customers and customers. They become a hallmark of e-commerce in creating attractiveness for customers.

AI-Based IoT Analytics on the Cloud for Diabetic Data Management System

2022 ◽  
pp. 143-161
Author(s):  
S. V. K. R. Rajeswari ◽  
Vijayakumar Ponnusamy
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Data Management ◽  
Human Body ◽  
Management System ◽  
Data Analytics ◽  
Current Data ◽  
Data Management System ◽  
Future Trends ◽  
Healthcare Application

It is very evident by looking at the current technological advancements that the interrelation and association of artificial intelligence (AI) and IoT in the Cloud have transformed the way healthcare has been working. AI and Cloud-empowered IoT boosts operational efficiency enhanced risk management. This combination creates products and services by enhancing the existing products while increasing scalability. To reduce costs, data analytics on the Cloud is much preferred in the current formation of technologies. This chapter focuses on the integration of different AI techniques in Cloud datasets for IoT data analytics. Analyzing, predicting, and making decisions by comparing the current data with historical data. The theory of AI-based IoT analytics will be much investigated with a healthcare application. Different approaches to implementing data analytics on the Cloud for a diabetic management system will be explored (human body). Finally, future trends and possible areas of research are also discussed.

Guiding ultrasound image capture with artificial intelligence

The Lancet ◽  
2020 ◽  
Vol 396 (10253) ◽  
pp. 749 ◽  
Author(s):  
Evan D Muse ◽  
Eric J Topol
Keyword(s):  
Artificial Intelligence ◽  
Ultrasound Image ◽  
Image Capture

scholarly journals Artificial Intelligence and Machine Learning in Orthopedic Surgery: A Systematic Review Protocol

2020 ◽  
Author(s):  
Nicola Maffulli ◽  
Hugo C. Rodriguez ◽  
Ian W. Stone ◽  
Andrew Nam ◽  
Albert Song ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Systematic Review ◽  
Clinical Diagnosis ◽  
Systematic Reviews ◽  
Orthopedic Surgery ◽  
Case Reports ◽  
Clinical Care ◽  
Primary Objective ◽  
Operative Outcomes

Abstract Background: Artificial Intelligence (AI) and Machine Learning (ML) is interwoven into our everyday lives and has grown enormously in some major fields in medicine including cardiology and radiology. While these specialties have quickly embraced AI and ML, orthopedic surgery has been slower to do so. Fortunately, there has been a recent surge in new research emphasizing the need for a systematic review. The primary objective of this systematic review will be to provide an update on the advances of AI and ML in the field of orthopedic surgery. The secondary objectives will be to evaluate the applications of AI and ML in providing a clinical diagnosis and predicting post-operative outcomes and complications in orthopedic surgery.Methods: A systematic search will be conducted in PubMed, ScienceDirect, and Google Scholar databases for articles written in English, Italian, French, Spanish and Portuguese language articles published up to September 2020. References will be screened and assessed for eligibility by at least two independent reviewers as per PRISMA guidelines. Studies must apply to orthopedic interventions, acute and chronic orthopedic musculoskeletal injuries to be considered eligible. Studies will be excluded if they are animal studies, do not relate to orthopedic interventions, or if no clinical data were produced. Gold standard processes and practices to obtain a clinical diagnosis and predict post-operative outcomes shall be compared with and without the use of ML algorithms. Any case reports and other primary studies assessing the prediction rate of post-operative outcomes or the ability to identify a diagnosis in orthopedic surgery will be included. Systematic reviews or literature reviews will be examined to identify further studies for inclusion, and results of meta-analyses will not be included in the analysis.Discussion: Our findings will evaluate the advances of AI and ML in the field of orthopedic surgery. We expect to find a large quantity of uncontrolled studies, and a smaller subset of articles describing actual applications and outcomes for clinical care. Cohort studies and large randomized control trial will likely be needed.Trial registration: The Protocol will be registered on PROSPERO international prospective register of systematic reviews prior to commencement.

scholarly journals COVID-19 and Artificial Intelligence: the pandemic pacifier

2020 ◽  
Vol 10 (4) ◽  
pp. 919-922
Author(s):  
Indrajit Banerjee ◽  
Jared Robinson ◽  
Abhishek Kashyap ◽  
Poornasha Mohabeer ◽  
Brijesh Sathian
Keyword(s):  
Artificial Intelligence ◽  
Human Performance ◽  
Industrial Revolution ◽  
System Development ◽  
Current Data ◽  
Rapid Screening ◽  
Contact Tracing ◽  
Data Systems ◽  
Surveillance Technology ◽  
The Government

COVID-19 remains a threat to the entire world. In an attempt to curb its spread and facilitate its treatment, the technological tool that is Artificial Intelligence (AI) is being researched as a potential alternative to conventional methods. Industrial Revolution 4.0 marks the dawn to the combination of digital, physical and biological systems, by application of digital skills such as Blockchain, Internet of things, Artificial Intelligence and Big data. AI tools in SARS-COV-2 pandemic are highly competitive to human performance, such as rapid screening and diagnosis of the disease, surveilling the efficacy of the treatment, keeping record and depicting active cases and mortality, inventions of medications and vaccines, relieving the workload of healthcare workers and extinguishing the spread of the disease. Contact tracing platforms like Aarogya Setu App, implemented by the Government of India, Australian Government's COVID Safe app, Trace Together- a Bluetooth-based contact tracing app developed in Singapore; based on syndromic mapping/surveillance technology. Artificial intelligence will become a mainstay in both the diagnosis and treatment of COVID-19 as well as similar pandemics in future. The application and system development will be challenging; the accuracy and rapidity of its use far outweigh this drawback. The current global technological leaders have proven that the retro modification of current data systems and applications have been indispensable in the war on COVID-19, thus permanently securing their development and application in future.

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