scholarly journals Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach

Author(s):  
Richard Threlkeld ◽  
Lirim Ashiku ◽  
Casey Canfield ◽  
Daniel B. Shank ◽  
Mark A. Schnitzler ◽  
...  

Abstract Purpose of Review A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard. Recent Findings Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and transplant healthcare. A systems approach leverages techniques for visualizing the system architecture to support solution design from multiple perspectives. Summary Developing a systems-based approach to AI decision support involves engaging in a cycle of documenting the system architecture, identifying pain points, developing prototypes, and validating the system. Early efforts have focused on describing process issues to prioritize tasks that would benefit from AI support.

2020 ◽  
Author(s):  
Avishek Choudhury

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.


2019 ◽  
Vol 42 (3) ◽  
pp. 771-779 ◽  
Author(s):  
Tayyebe Shabaniyan ◽  
Hossein Parsaei ◽  
Alireza Aminsharifi ◽  
Mohammad Mehdi Movahedi ◽  
Amin Torabi Jahromi ◽  
...  

2021 ◽  
Vol 26 (1) ◽  
pp. 87-93
Author(s):  
Sandeep Patalay ◽  
Madhusudhan Rao Bandlamudi

Investing in stock market requires in-depth knowledge of finance and stock market dynamics. Stock Portfolio Selection and management involve complex financial analysis and decision making policies. An Individual investor seeking to invest in stock portfolio is need of a support system which can guide him to create a portfolio of stocks based on sound financial analysis. In this paper the authors designed a Financial Decision Support System (DSS) for creating and managing a portfolio of stock which is based on Artificial Intelligence (AI) and Machine learning (ML) and combining the traditional approach of mathematical models. We believe this a unique approach to perform stock portfolio, the results of this study are quite encouraging as the stock portfolios created by the DSS are based on strong financial health indices which in turn are giving Return on Investment (ROI) in the range of more than 11% in the short term and more than 61% in the long term, therefore beating the market index by a factor of 15%. This system has the potential to help millions of Individual Investors who can make their financial decisions on stocks and may eventually contribute to a more efficient financial system.


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