The Adoption of Artificial Intelligence in the E-Commerce Trade of Healthcare Industry

2021 ◽  
pp. 75-88
Author(s):  
Yan Kong ◽  
Yilin Hou ◽  
Shiwei Sun
Keyword(s):  
Artificial Intelligence ◽  
Healthcare Industry

scholarly journals Controlling Safety of Artificial Intelligence-Based Systems in Healthcare

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 102
Author(s):  
Mohammad Reza Davahli ◽  
Waldemar Karwowski ◽  
Krzysztof Fiok ◽  
Thomas Wan ◽  
Hamid R. Parsaei
Keyword(s):  
Artificial Intelligence ◽  
Rating Scale ◽  
Black Box ◽  
Healthcare Industry ◽  
Emergency Plans ◽  
Controlling System ◽  
Box Models ◽  
Key Dimensions ◽  
Value Model ◽  
And Control

In response to the need to address the safety challenges in the use of artificial intelligence (AI), this research aimed to develop a framework for a safety controlling system (SCS) to address the AI black-box mystery in the healthcare industry. The main objective was to propose safety guidelines for implementing AI black-box models to reduce the risk of potential healthcare-related incidents and accidents. The system was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. On the basis of the MAVT approach, three layers of attributes were created. The first level contained six key dimensions, the second level included 14 attributes, and the third level comprised 78 attributes. The key first level dimensions of the SCS included safety policies, incentives for clinicians, clinician and patient training, communication and interaction, planning of actions, and control of such actions. The proposed system may provide a basis for detecting AI utilization risks, preventing incidents from occurring, and developing emergency plans for AI-related risks. This approach could also guide and control the implementation of AI systems in the healthcare industry.

The Rise and Application of Artificial Intelligence in Healthcare

2021 ◽  
pp. 28-49
Author(s):  
Ivan Khoo Yi ◽  
Andrew Fang Hao Sen
Keyword(s):  
Artificial Intelligence ◽  
Financial Institutions ◽  
Molecular Level ◽  
Healthcare Providers ◽  
Pharmaceutical Companies ◽  
Healthcare Industry ◽  
Practice Of Medicine ◽  
Potential Benefits ◽  
Legal Professional ◽  
Medical Domain

The overall purpose of this chapter will be to broadly explore both the existing and possible implementations of artificial intelligence (AI) in healthcare. The scope of this chapter will be explored from the unique perspectives of various stakeholders in the healthcare industry, namely the healthcare providers, patients, pharmaceutical companies, healthcare financial institutions, and policymakers. The chapter will seek to identify the potential benefits and pitfalls that faced by these stakeholders in implementing the use of AI, from the molecular level to a macroeconomics level; as well as seeking to understand the legal, professional, and ethical boundaries of the medical domain that are challenged as AI increasingly becomes irreversibly intertwined with the practice of medicine.

Features

2019 ◽  
Vol 23 (08) ◽  
pp. 34-51
Keyword(s):  
Artificial Intelligence ◽  
Life Sciences ◽  
Healthcare Industry ◽  
The Future ◽  
Lifestyle Diseases

The following topics are under this section: The future of predicting lifestyle diseases is here in Asia Breaking Barriers for Artificial Intelligence (AI) in Healthcare: bridging vision and reality with the language of trust Overcoming Challenges of Managing Information in Life Sciences, Towards the Digital Future Under the Weather: Cybersecurity Woes in the healthcare Industry

scholarly journals Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

2019 ◽  
Vol 8 (1) ◽  
pp. 382
Author(s):  
Rahul Badwaik
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Setting ◽  
Digital Transformation ◽  
Current Status ◽  
Healthcare Industry ◽  
Review Of The Literature

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed.

scholarly journals Artificial Intelligence for Healthcare in India

2021 ◽  
Vol 16 (4) ◽  
pp. 1-11
Author(s):  
Sheshadri Chatterjee ◽  
Michael S. Dohan
Keyword(s):  
Artificial Intelligence ◽  
Healthcare System ◽  
Qualitative Approach ◽  
Healthcare Sector ◽  
Healthcare Industry ◽  
Policy Makers ◽  
Proper Actions ◽  
Policy Initiatives ◽  
The Government ◽  
Applications Of Ai

The purpose of the paper is to provide an overview of the issues related to Artificial Intelligence (AI) applications in the Indian healthcare sector and provide input to policy makers. A qualitative approach has been used in this study to identify government initiatives, opportunities and challenges for applications of AI. , and suggests improvements in policy areas relevant to AI in healthcare. The study helps by providing comprehensive inputs for framing policy on AI in healthcare industry in India. The study also highlights that that if the proper actions are taken to overcome the various challenges associated with applications of AI in healthcare sector in India by the government, then the healthcare sector will immensely benefit. This article has taken an attempt to provide inputs concerning to policy initiatives, challenges and recommendations for improving healthcare system of India using different applications of AI.

scholarly journals Adoption of machine learning for medical diagnosis

2021 ◽  
Author(s):  
Mohammed Yousef Shaheen
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Chronic Diseases ◽  
Medical Diagnosis ◽  
Healthcare Industry ◽  
Early Adopter ◽  
Medical Treatments ◽  
Health Related ◽  
Detection And Diagnosis ◽  
Diagnosis Of Diseases

The healthcare industry has historically been an early adopter of technology advancements and has reaped significant benefits. Machine learning (an artificial intelligence subset) is being used in a variety of health-related fields, including the invention of new medical treatments, the management of patient data and records, and the treatment of chronic diseases. One of the most important uses of machine learning in healthcare is the detection and diagnosis of diseases and conditions that are otherwise difficult to identify. This can range from tumors that are difficult to detect in their early stages to other hereditary illnesses. This research identifies and discusses the various usages of machine learning in medical diagnosis.

scholarly journals Impact of Artificial Intelligence on the Healthcare Industry

2020 ◽  
Vol 15 (2) ◽  
pp. 59-65
Author(s):  
Birendra Mishra ◽  
Zubin Mishra ◽  
Oldooz Aloosh
Keyword(s):  
Artificial Intelligence ◽  
Healthcare Industry

Patentability challenges associated with emerging pharmaceutical technologies

2021 ◽  
Author(s):  
Srishti Aggarwal ◽  
Amrish Chandra
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Stem Cell ◽  
Personalized Medicine ◽  
Cell Therapy ◽  
Emerging Technologies ◽  
Healthcare Industry ◽  
Biological Therapies ◽  
Patent Laws ◽  
Patent Filing

According to the recent patent filing trends, it has been observed that certain pharmaceutical technologies are more popular than others and are commonly referred to as emerging technologies. The emerging technologies in the pharmaceutical sector include artificial intelligence, big data and certain advanced biological therapies such as personalized medicine and stem cell therapy. These trends have various applications in the medicine and healthcare industry. Since these technologies are relatively new and each of them is very unique in its own way, current patent laws are inadequate to deal with the complex challenges associated with them. A brief analysis of the challenges associated with these emerging technologies and their applications is discussed in this paper.

AI-Driven Big Healthcare Analytics

2021 ◽  
pp. 172-184
Author(s):  
Faiz Maazouzi ◽  
Hafed Zarzour
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Centers ◽  
Medical Data ◽  
Healthcare Industry ◽  
Healthcare Organizations ◽  
Healthcare Analytics ◽  
Digital Contents ◽  
Patients At Risk ◽  
Medical Big Data

With the increased development of technology in healthcare, a huge amount of data is collected from healthcare organizations and stored in distributed medical data centers. In this context, such data quantities, called medical big data, which include different types of digital contents such as text, image, and video, have become an interesting topic tending to change the way we describe, manage, process, analyze, and visualize data in healthcare industry. Artificial intelligence (AI) is one of the sub-fields of computer science enabling us to analyze and solve more complex problems in many areas, including healthcare. AI-driven big healthcare analytics have the potential to predict patients at risk, spread of viruses like SARS-CoV-2, spread of new coronavirus, diseases, and new potential drugs. This chapter presents the AI-driven big healthcare analytics as well as discusses the benefits and the challenges. It is expected that the chapter helps researchers and practitioners to apply AI and big data to improve healthcare.

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