scholarly journals Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age

2019 ◽  
Vol 48 (1) ◽  
pp. 77-83 ◽  
Author(s):  
R. Patcas ◽  
D.A.J. Bernini ◽  
A. Volokitin ◽  
E. Agustsson ◽  
R. Rothe ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Facial Attractiveness ◽  
The Impact

Facial attractiveness of cleft patients: a direct comparison between artificial-intelligence-based scoring and conventional rater groups

2019 ◽  
Vol 41 (4) ◽  
pp. 428-433 ◽  
Author(s):  
Raphael Patcas ◽  
Radu Timofte ◽  
Anna Volokitin ◽  
Eirikur Agustsson ◽  
Theodore Eliades ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Visual Analogue Scale ◽  
Convolutional Neural Networks ◽  
Analogue Scale ◽  
Facial Attractiveness ◽  
Helpful Tool ◽  
The Impact ◽  
Strong Agreement

Summary Objectives To evaluate facial attractiveness of treated cleft patients and controls by artificial intelligence (AI) and to compare these results with panel ratings performed by laypeople, orthodontists, and oral surgeons. Materials and methods Frontal and profile images of 20 treated left-sided cleft patients (10 males, mean age: 20.5 years) and 10 controls (5 males, mean age: 22.1 years) were evaluated for facial attractiveness with dedicated convolutional neural networks trained on >17 million ratings for attractiveness and compared to the assessments of 15 laypeople, 14 orthodontists, and 10 oral surgeons performed on a visual analogue scale (n = 2323 scorings). Results AI evaluation of cleft patients (mean score: 4.75 ± 1.27) was comparable to human ratings (laypeople: 4.24 ± 0.81, orthodontists: 4.82 ± 0.94, oral surgeons: 4.74 ± 0.83) and was not statistically different (all Ps ≥ 0.19). Facial attractiveness of controls was rated significantly higher by humans than AI (all Ps ≤ 0.02), which yielded lower scores than in cleft subjects. Variance was considerably large in all human rating groups when considering cases separately, and especially accentuated in the assessment of cleft patients (coefficient of variance—laypeople: 38.73 ± 9.64, orthodontists: 32.56 ± 8.21, oral surgeons: 42.19 ± 9.80). Conclusions AI-based results were comparable with the average scores of cleft patients seen in all three rating groups (with especially strong agreement to both professional panels) but overall lower for control cases. The variance observed in panel ratings revealed a large imprecision based on a problematic absence of unity. Implication Current panel-based evaluations of facial attractiveness suffer from dispersion-related issues and remain practically unavailable for patients. AI could become a helpful tool to describe facial attractiveness, but the present results indicate that important adjustments are needed on AI models, to improve the interpretation of the impact of cleft features on facial attractiveness.

Trading faces: Complete AI face doubles avoid the uncanny valley

2020 ◽  
Author(s):  
Christopher Welker ◽  
David France ◽  
Alice Henty ◽  
Thalia Wheatley
Keyword(s):  
Artificial Intelligence ◽  
Sexual Orientation ◽  
Uncanny Valley ◽  
Torture Survivors ◽  
The Uncanny ◽  
The Creation ◽  
Full Face ◽  
The Impact

Advances in artificial intelligence (AI) enable the creation of videos in which a person appears to say or do things they did not. The impact of these so-called “deepfakes” hinges on their perceived realness. Here we tested different versions of deepfake faces for Welcome to Chechnya, a documentary that used face swaps to protect the privacy of Chechen torture survivors who were persecuted because of their sexual orientation. AI face swaps that replace an entire face with another were perceived as more human-like and less unsettling compared to partial face swaps that left the survivors’ original eyes unaltered. The full-face swap was deemed the least unsettling even in comparison to the original (unaltered) face. When rendered in full, AI face swaps can appear human and avoid aversive responses in the viewer associated with the uncanny valley.

Artificial Intelligence as a Business Partner in Cardiovascular Precision Medicine: an Emerging Approach for Disease Detection and Treatment Optimization

2020 ◽  
Vol 28 ◽  
Author(s):  
Valeria Visco ◽  
Germano Junior Ferruzzi ◽  
Federico Nicastro ◽  
Nicola Virtuoso ◽  
Albino Carrizzo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Heart Failure ◽  
Atrial Fibrillation ◽  
Precision Medicine ◽  
Clinical Decision Making ◽  
Disease Detection ◽  
Physician Patient Relationship ◽  
Invasive Approach ◽  
Tailored Treatment ◽  
The Impact

Background: In the real world, medical practice is changing hand in hand with the development of new Artificial Intelligence (AI) systems and problems from different areas have been successfully solved using AI algorithms. Specifically, the use of AI techniques in setting up or building precision medicine is significant in terms of the accuracy of disease discovery and tailored treatment. Moreover, with the use of technology, clinical personnel can deliver a very much efficient healthcare service. Objective: This article reviews AI state-of-the-art in cardiovascular disease management, focusing on diagnostic and therapeutic improvements. Methods: To that end, we conducted a detailed PubMed search on AI application from distinct areas of cardiology: heart failure, arterial hypertension, atrial fibrillation, syncope and cardiovascular rehabilitation. Particularly, to assess the impact of these technologies in clinical decision-making, this research considers technical and medical aspects. Results: On one hand, some devices in heart failure, atrial fibrillation and cardiac rehabilitation represent an inexpensive, not invasive or not very invasive approach to long-term surveillance and management in these areas. On the other hand, the availability of large datasets (big data) is a useful tool to predict the development and outcome of many cardiovascular diseases. In summary, with this new guided therapy, the physician can supply prompt, individualised, and tailored treatment and the patients feel safe as they are continuously monitored, with a significant psychological effect. Conclusion: Soon, tailored patient care via telemonitoring can improve the clinical practice because AI-based systems support cardiologists in daily medical activities, improving disease detection and treatment. However, the physician-patient relationship remains a pivotal step.

Artificial Intelligence and Inequality in the Middle East

2020 ◽  
pp. 624-649 ◽  
Author(s):  
Nagla Rizk
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
Young Population ◽  
Mena Region ◽  
Poor Countries ◽  
Current State ◽  
Resource Poor ◽  
Youth Entrepreneurship ◽  
The Arab Spring ◽  
The Impact

This chapter looks at the challenges, opportunities, and tensions facing the equitable development of artificial intelligence (AI) in the MENA region in the aftermath of the Arab Spring. While diverse in their natural and human resource endowments, countries of the region share a commonality in the predominance of a youthful population amid complex political and economic contexts. Rampant unemployment—especially among a growing young population—together with informality, gender, and digital inequalities, will likely shape the impact of AI technologies, especially in the region’s labor-abundant resource-poor countries. The chapter then analyzes issues related to data, legislative environment, infrastructure, and human resources as key inputs to AI technologies which in their current state may exacerbate existing inequalities. Ultimately, the promise for AI technologies for inclusion and helping mitigate inequalities lies in harnessing grounds-up youth entrepreneurship and innovation initiatives driven by data and AI, with a few hopeful signs coming from national policies.

The impact of artificial intelligence and big data on end-stage kidney disease treatments

2021 ◽  
pp. 115076
Author(s):  
Covadonga Díez-Sanmartín ◽  
Antonio Sarasa-Cabezuelo ◽  
Amado Andrés Belmonte
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Kidney Disease ◽  
End Stage Kidney Disease ◽  
End Stage ◽  
The Impact

scholarly journals Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Expert System ◽  
Population Monitoring ◽  
High Definition ◽  
Contagious Diseases ◽  
The World ◽  
General Guide ◽  
The Impact ◽  
Back To Work

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.

Sign in / Sign up

Export Citation Format

Share Document