scholarly journals How Can Artificial Intelligence Make Medicine More Preemptive?

10.2196/17211 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e17211
Author(s):  
Usman Iqbal ◽  
Leo Anthony Celi ◽  
Yu-Chuan Jack Li
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Big Data ◽  
Early Detection ◽  
Cost Effective ◽  
Screening Tools ◽  
Early Detection Of Disease ◽  
New Era ◽  
Predictive Approach ◽  
Data Screening

In this paper we propose the idea that Artificial intelligence (AI) is ushering in a new era of “Earlier Medicine,” which is a predictive approach for disease prevention based on AI modeling and big data. The flourishing health care technological landscape is showing great potential—from diagnosis and prescription automation to the early detection of disease through efficient and cost-effective patient data screening tools that benefit from the predictive capabilities of AI. Monitoring the trajectories of both in- and outpatients has proven to be a task AI can perform to a reliable degree. Predictions can be a significant advantage to health care if they are accurate, prompt, and can be personalized and acted upon efficiently. This is where AI plays a crucial role in “Earlier Medicine” implementation.

scholarly journals Correction: How Can Artificial Intelligence Make Medicine More Preemptive? (Preprint)

2020 ◽  
Author(s):  
Usman Iqbal ◽  
Leo Anthony Celi ◽  
Yu-Chuan Jack Li
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Big Data ◽  
Early Detection ◽  
Cost Effective ◽  
Screening Tools ◽  
Early Detection Of Disease ◽  
New Era ◽  
Predictive Approach ◽  
Data Screening

UNSTRUCTURED In this paper we propose the idea that Artificial intelligence (AI) is ushering in a new era of “Earlier Medicine,” which is a predictive approach for disease prevention based on AI modeling and big data. The flourishing health care technological landscape is showing great potential—from diagnosis and prescription automation to the early detection of disease through efficient and cost-effective patient data screening tools that benefit from the predictive capabilities of AI. Monitoring the trajectories of both in- and outpatients has proven to be a task AI can perform to a reliable degree. Predictions can be a significant advantage to health care if they are accurate, prompt, and can be personalized and acted upon efficiently. This is where AI plays a crucial role in “Earlier Medicine” implementation.

scholarly journals How Can Artificial Intelligence Make Medicine More Preemptive? (Preprint)

2019 ◽  
Author(s):  
Usman Iqbal ◽  
Leo Anthony Celi ◽  
Yu-Chuan Jack Li
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Big Data ◽  
Early Detection ◽  
Cost Effective ◽  
Screening Tools ◽  
Early Detection Of Disease ◽  
New Era ◽  
Predictive Approach ◽  
Data Screening

UNSTRUCTURED In this paper we propose the idea that Artificial intelligence (AI) is ushering in a new era of “Earlier Medicine,” which is a predictive approach for disease prevention based on AI modeling and big data. The flourishing health care technological landscape is showing great potential—from diagnosis and prescription automation to the early detection of disease through efficient and cost-effective patient data screening tools that benefit from the predictive capabilities of AI. Monitoring the trajectories of both in- and outpatients has proven to be a task AI can perform to a reliable degree. Predictions can be a significant advantage to health care if they are accurate, prompt, and can be personalized and acted upon efficiently. This is where AI plays a crucial role in “Earlier Medicine” implementation.

scholarly journals How Do Machines Learn? Artificial Intelligence as a New Era in Medicine

2021 ◽  
Vol 11 (1) ◽  
pp. 32
Author(s):  
Oliwia Koteluk ◽  
Adrian Wartecki ◽  
Sylwia Mazurek ◽  
Iga Kołodziejczak ◽  
Andrzej Mackiewicz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Medical Data ◽  
General Process ◽  
New Era ◽  
Automated Evaluation ◽  
Machine Learning Applications ◽  
And Training ◽  
Current Standards

With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to make faster and more correct decisions and improving current standards of treatment. Today, machines can analyze, learn, communicate, and understand processed data and are used in health care increasingly. This review explains different models and the general process of machine learning and training the algorithms. Furthermore, it summarizes the most useful machine learning applications and tools in different branches of medicine and health care (radiology, pathology, pharmacology, infectious diseases, personalized decision making, and many others). The review also addresses the futuristic prospects and threats of applying artificial intelligence as an advanced, automated medicine tool.

scholarly journals A Data-Driven Platform to Computer Performance Analysis and Recommendation using AI and Big Data Analysis

2021 ◽  
Author(s):  
Shuo Chen ◽  
Yu Sun
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Qualitative Evaluation ◽  
Cost Effective ◽  
Big Data Analysis ◽  
Data Driven ◽  
Computer Performance ◽  
Time And Energy ◽  
Artificial Intelligence Application ◽  
Intelligence Application

When I was assembling the computer, I found a problem. This problem is that we need to spend a lot of time and energy when we choose a desktop with a configuration and price that we are satisfied with [5]. Some computer websites will only recommend some ordinary desktops to users. Does not allow users to get what they really want, and some other shops that assemble computer mainframes use the characteristics of customers that do not understand computers to increase prices. So I wanted to create a software to help these people who need to assemble a computer to find the most suitable computer efficiently and in accordance with their requirements [6]. This program, according to the needs of users, artificial intelligence application crawler technology can help users find the most suitable computer parts based on big data, and help users get the most cost-effective self-assembled computer host. We applied our application to match a person in need of a computer host with My Platform and conducted a qualitative evaluation of the method [7]. The results showed that My Platform can efficiently and quality match the user's needs and find the best solution for the user.

Artificial Intelligence and SHGs

2020 ◽  
pp. 291-303
Author(s):  
Vinay Kandpal ◽  
Osamah Ibrahim Khalaf
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Big Data ◽  
Financial Services ◽  
Efficient Solution ◽  
Cost Effective ◽  
Financial Inclusion ◽  
Women Empowerment ◽  
Loan Repayment ◽  
Brick And Mortar

For inclusive growth and sustainable development of SHG and women empowerment, there is a need to provide an environment to access quality services from financial and non-financial agencies. While banks cannot reach all people through a ‘brick and mortar' model, new and advanced banking technology has enabled financial inclusion through branchless banking. By using artificial intelligence in banking, banks have a cost-effective and efficient solution to provide access to services to the financially excluded. Digital technology improves the accessibility and affordability of financial services for the previously unbanked or underbanked individuals and MSMEs. A big data-driven model can also be helpful for psychometric evaluations. Several psychometric tools help evaluate the applicant's answers which aid to capture information that can help to predict loan repayment behavior, comprising applicants' beliefs, performance, attitudes, and integrity.

scholarly journals Artificial Intelligent in Healthcare

2019 ◽  
Vol 11 (2) ◽  
pp. 125-35
Author(s):  
Anna Meiliana ◽  
Nurrani Mustika Dewi ◽  
Andi Wijaya
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Big Data ◽  
Complex Disease ◽  
Disease Diagnosis ◽  
Large Set ◽  
Health Records ◽  
Treatment Data ◽  
Precision Health

BACKGROUND: Giant transformations are going on currently in health care, and the greatest force behind this phenomenon is data.CONTENT: Big data has arrived into medicine field, lead to potential enhancement in accountability, quality, efficiency, and innovation. Most updated, artificial intelligence (AI) and machine-learning (ML) techniques rapidly developed, bring forth the big data analysis into more useful applications, from resource allocation to complex disease diagnosis. To realize this, a very large set of health-care data is needed for algorithms training and evaluation, including patients’ treatment data, patients respond to treatment, and personal patient information, such as genetic data, family history, health behavior, and vital signs.SUMMARY: Precision Health involving preventive, predictive, personalized and precise. The arrival of AI and ML will enhance and facilitates the improvement of this relationship through better accuracy, productivity, and workflow, thus develop a health system that will go beyond just curing disease, but further into wellness that preventing disease before it strikes, thus the patient–doctor bond is expected to be reformed and not be eroded.KEYWORDS: artificial intelligence, machine learning, deep learning, electronic health records, big data

scholarly journals Learning from Artificial Intelligence and Big Data in Health Care

2020 ◽  
Vol 59 (6) ◽  
pp. 868-869 ◽  
Author(s):  
Jean-B. Ricco ◽  
Farid Guetarni ◽  
Philippe Kolh
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Big Data
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