scholarly journals Artificial intelligence in dermatology

2020 ◽  
Vol 0 ◽  
pp. 1-4
Author(s):  
Amitha Abraham ◽  
K. Sobhanakumari ◽  
Athira Mohan
Keyword(s):  
Artificial Intelligence ◽  
Risk Assessment ◽  
Medical Care ◽  
Implementation Barriers ◽  
New Applications

Artificial intelligence (AI) refers to the ability of a machine to communicate, reason, and operate independently. There is a need to understand this technology’s progress for future medical care. AI has many applications in the field of medicine, but its use in dermatology is comparatively new. Applications that commonly analyse and classify images and tools like risk assessment calculators are available. Even though many applications exist, the important implementation barriers inclue difficulty in standardization, interpretability, and acceptance by patient and doctor.

scholarly journals The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?

Healthcare ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 30
Author(s):  
Daniele Giansanti
Keyword(s):  
Artificial Intelligence ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Mobile Health ◽  
Digital Pathology ◽  
Digital Radiology ◽  
Cellular Diagnostics ◽  
Information And Communication ◽  
Electronic Health ◽  
New Applications

Thanks to the incredible changes promoted by Information and Communication Technology (ICT) conveyed today by electronic-health (eHealth) and mobile-health (mHealth), many new applications of both organ and cellular diagnostics are now possible [...]

AIRA, an Artificial Intelligence Realistic Assistant that will save your time, a before-and-after study during Pandemic (Preprint)

2021 ◽  
Author(s):  
Kaio Bin ◽  
Adler Araújo Ribeiro Melo ◽  
José Guilherme Franco Da Rocha ◽  
Renata Pivi De Almeida ◽  
Vilson Cobello Junior ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Record ◽  
Medical Care ◽  
Health Screening ◽  
Urgent Care ◽  
Health Record ◽  
Before And After ◽  
Electronic Health ◽  
The Impact ◽  
Before And After Study

BACKGROUND AIRA is an AI designed to reduce the time that doctors dedicate filling out EHR, winner of the first edition of MIT Hacking Medicine held in Brazil in 2020. As a proof of concept, AIRA was implemented in administrative process before its application in a medical process. OBJECTIVE The aim of the study is to determinate the impact of AIRA by eliminating the Medical Care Registration (MCR) on Electronic Health Record (EHR) by Administrative Officer. METHODS This is a comparative before-and-after study following the guidance “Evaluating digital health products” from Public Health England. An Artificial Intelligence named AIRA was created and implemented at CEAC (Employee Attention Center) from HCFMUSP. A total of 25,507 attendances were evaluated along 2020 for determinate AIRA´s impact. Total of MCR, time of health screening and time between the end of the screening and the beginning of medical care, were compared in the pre and post AIRA periods. RESULTS AIRA eliminated the need for Medical Care Registration by Administrative Officer in 92% (p<0.0001). The nurse´s time of health screening increased 16% (p<0.0001) during the implementation, and 13% (p<0.0001) until three months after the implementation, but reduced in 4% three months after implementation (p<0.0001). The mean and median total time to Medical Care after the nurse’ Screening was decreased in 30% (p<0.0001) and 41% (p<0.0001) respectively. CONCLUSIONS The implementation of AIRA reduced the time to medical care in an urgent care after the nurse´ screening, by eliminating non-value-added activity the Medical Care Registration on Electronic Health Record (EHR) by Administrative Officer.

Making algorithms safe for workers: occupational risks associated with work managed by artificial intelligence

2021 ◽  
pp. 102425892110350
Author(s):  
Adrián Todolí-Signes
Keyword(s):  
Artificial Intelligence ◽  
Risk Assessment ◽  
Health And Safety ◽  
Health Hazards ◽  
Risk Prevention ◽  
Occupational Risks ◽  
Technological Management

It is increasingly common for companies to use artificial intelligence mechanisms to manage work. This study examines the health hazards caused by these new forms of technological management. Occupational risks can be reduced if they are taken into account when programming an algorithm. This study confirms the need for algorithms to be correctly programmed, taking account of these occupational risks. In the same way as supervisors have to be trained in risk prevention to be able to perform their work, the algorithm must be programmed to weigh up the occupational risks – and when such features do not exist, steps must be taken to prevent the algorithm being used to direct workers. The algorithm must assess all (known) factors posing a risk to workers’ health and safety. It therefore seems necessary to incorporate a mandatory risk assessment performed by specialists in the programming of algorithms so that all ascertained risks can be taken into account.

scholarly journals New Applications of the Annual Fiscal Accounting Analysis at the Risk Assessment

2019 ◽  
Author(s):  
Alexander Alekseev ◽  
Irina Alekseeva ◽  
Alexandra Noskova ◽  
Victoriya Kylosova ◽  
Alena Knyazeva
Keyword(s):  
Risk Assessment ◽  
New Applications

scholarly journals The place of artificial intelligence in the risk management process

2021 ◽  
Vol 120 ◽  
pp. 02013
Author(s):  
Petya Biolcheva
Keyword(s):  
Artificial Intelligence ◽  
Risk Assessment ◽  
Risk Management ◽  
Real Time ◽  
Risk Identification ◽  
Management Process ◽  
Whole Process ◽  
Risk Management Process ◽  
Problematic Issue ◽  
The Individual

In recent years, there has been increasing talk of the rapid entry of artificial intelligence into risk management. All the benefits it would bring over the whole process are often commented on: real-time results, processing large amounts of data, more complete risk identification, more accurate risk assessment, etc. There are also negative moods that make various experts feel threatened by their need to be replaced by artificial intelligence. Another problematic issue that arises is related to the transparency of algorithms and the increase in cyber risks [6]. This material aims to identify the individual elements at the stages of risk management in which artificial intelligence (AI) can and should be applied alone, in combination with expert opinion or not. Here it is shown that because of the use of AI the efficiency of the whole process is significantly increased, first of all by conducting in-depth analyses, and the decisions are made by the risk management experts. This proves its usefulness and increases the confidence of experts in it.

Conclusion

2020 ◽  
pp. 97-102
Author(s):  
Benjamin Wiggins
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Risk Assessment ◽  
Big Data ◽  
The United States ◽  
Blaise Pascal ◽  
Division Problem ◽  
The World

Can risk assessment be made fair? The conclusion of Calculating Race returns to actuarial science’s foundations in probability. The roots of probability rest in a pair of problems posed to Blaise Pascal and Pierre de Fermat in the summer of 1654: “the Dice Problem” and “the Division Problem.” From their very foundation, the mathematics of probability offered the potential not only to be used to gain an advantage (as in the case of the Dice Problem), but also to divide material fairly (as in the case of the Division Problem). As the United States and the world enter an age driven by Big Data, algorithms, artificial intelligence, and machine learning and characterized by an actuarialization of everything, we must remember that risk assessment need not be put to use for individual, corporate, or government advantage but, rather, that it has always been capable of guiding how to distribute risk equitably instead.

scholarly journals Artificial Intelligence Based Commercial Risk Management Framework for SMEs

2019 ◽  
Vol 11 (16) ◽  
pp. 4501
Author(s):  
Gerda Žigienė ◽  
Egidijus Rybakovas ◽  
Robertas Alzbutas
Keyword(s):  
Artificial Intelligence ◽  
Risk Assessment ◽  
Risk Management ◽  
Academic Research ◽  
Building Blocks ◽  
Learning Technologies ◽  
Potential Contribution ◽  
Risk Management Framework ◽  
Development Goals ◽  
Risk Assessment And Management

Risk management in commercial processes is among the most important procedures affecting the competitiveness of small and medium-sized enterprises (SMEs), their innovativeness and potential contribution to global sustainable development goals (SDGs). The ecosystem of commercial processes is the prerequisite to manage risk faced by SMEs. Commercial risk assessment and management using elements of artificial intelligence, big data, and machine learning technologies could be developed and maintained as external services for a group of SMEs allowing to share costs and benefits. This paper aims to provide a conceptual framework of commercial risk assessment and management solution based on elements of artificial intelligence. This conceptualization is done on the background of scientific literature, policy documents, and risk management standards. Main building blocks of the framework in terms of commercial risk categories, data sources and workflow phases are presented in the article. Business companies, state policy, and academic research focused recommendations on the further development of the framework and its implementation are elaborated.

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