Instructions
Goal: Demonstrate the ability to create a final project that uses both research-based and personal content while using presentation software to communicate with an intended audience.
Description:
During the first six-weeks you formulated a project plan, researched the content of the plan, and collected quality academic and non-academic sources. For the week 7 Final Project you will create a presentation (CO8) that builds upon the Week 3 Project Plan and the Week 5 Location and Access (Source Organization worksheet) that effectively communicates the knowledge you have gained during COMM120.
Please consider the following:
- Presentation will include an introduction, body, conclusion, and properly formatted reference/work cited slide in the citation style of your degree program (APA).
- Clear evidence that the topic was researched and expanded upon the week 2 Project Plan (CO2 & 5).
- Presentation provides audience with information to increase their knowledge of the topic presented (CO1).
- Presentation engages the audience by using elements such as images, graphs, and charts. Appropriate citations must be included.
- Three (3) vetted credible sources. One (1) of the sources must be scholarly and from the library.
- Appropriate length 7-9 slides.
***Project Plan & Source Eval Sheet attached***
2
Source Evaluation Worksheet
Bryan Cridell
American Military University
Comm120 Information and Digital Literacy
Dr. Sarah Syrjanen
05 July 2023
Source Evaluation Worksheet
Part I: Topic
The Week 7 Field of Study Project focuses on applying artificial intelligence (AI) in healthcare. AI has emerged as a transformative technology with the potential to revolutionize various industries, and healthcare is no exception. It involves developing and implementing sophisticated algorithms and systems to evaluate vast medical data, generate accurate predictions, and support healthcare professionals in the diagnosis, treatment planning, and patient care. AI is used in medical imaging analysis, clinical decision support systems, virtual health assistants, drug discovery, and customized medicine. AI can increase diagnostic accuracy, treatment regimens, patient results, and lifesaving. AI algorithms can quickly and accurately evaluate medical pictures like X-rays, CT scans, and MRIs to find abnormalities, enabling early cancer identification. Doctors can make better-educated treatment decisions with AI-powered clinical decision support systems that examine patient data, medical records, and research material. AI-powered virtual health assistants may advise patients, monitor their health remotely, and provide individualized lifestyle counsel. AI can also analyze vast databases, identify medication candidates, and speed up development.
Part II: Source Evaluation
Article Title: The role of artificial intelligence in healthcare: a structured literature review
Article Author(s): Silvana Secinaro, Davide Calandra, Aurelio Secinaro, Vivek Muthurangu & Paolo Biancone
Retrieval Information (example website link): https://link.springer.com/article/10.1186/s12911-021-01488-9
Source’s Publication Date: 2021
Publishing Information: BMC Medical Informatics and Decision Making released "The role of artificial intelligence in healthcare: a structured literature review" on April 10, 2021. Silvana Secinaro, Davide Calandra, Aurelio, Vivek Muthurangu, and Paolo Biancone wrote the article. This open-access research article examines healthcare AI applications. An organized literature evaluation analyzes 288 Scopus peer-reviewed papers. Health services management, predictive medicine, patient data, diagnostics, and clinical decision-making are examined. The study sheds information on AI in healthcare and suggests future research.
Source Summary:
"The role of artificial intelligence in healthcare: a structured literature review" provides a detailed overview of healthcare AI applications. 288 Scopus-reviewed articles were analyzed in a structured literature study. The study shows that AI in healthcare is emerging in areas including health services management, predictive medicine, patient data analysis, diagnostics, and clinical decision-making. AI can help doctors detect, forecast disease spread, and customize treatment. The study underlines the need for skills and data quality awareness in AI projects and gives insights for healthcare researchers and practitioners. The article helps explain AI in healthcare.
Article Title: The potential for artificial intelligence in healthcare
Article Author(s): Thomas Davenport, Ravi Kalakota
Retrieval Information (example website link): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181/
Source’s Publication Date: 2019
Publishing Information: Future Health Journal released "The potential for artificial intelligence in healthcare" in June 2019. The article is in Volume 6, Issue 2, and spans pages 94-98. Thomas Davenport, President's Distinguished Professor of Information Technology and Management, and Ravi Kalakota, Managing Director, wrote the article. Due to data complexity and abundance, healthcare is increasingly using AI. Healthcare payers, providers, and life sciences businesses use AI applications. These apps cover diagnosis, therapy, patient interaction, and administration. The study notes that implementation factors may delay the widespread automation of healthcare professional positions for a long time, even though AI can outperform humans in some areas. The paper addresses healthcare AI ethics.
Source Summary:
Thomas Davenport and Ravi Kalakota's article "The potential for artificial intelligence in healthcare" highlights AI's growing significance in healthcare. The authors discuss machine learning, natural language processing, rule-based expert systems, physical robots, and robotic process automation. They underline AI's potential to automate healthcare administrative and patient care activities. AI applications include diagnosis and therapy, patient involvement and adherence, and administrative chores. AI has showed promise in disease diagnosis and therapy suggestions, but practical issues and ethical concerns prevent its widespread adoption. The article discusses AI in healthcare and its pros and cons.
Article Title: Artificial intelligence in healthcare: An essential guide for health leaders
Article Author(s): Mei Chen, Michel Decary
Retrieval Information (example website link): https://journals.sagepub.com/doi/pdf/10.1177/0840470419873123
Source’s Publication Date: 2021
Publishing Information: The article "Artificial intelligence in healthcare: An essential guide for health leaders" by Mei Chen, Ph.D., and Michel Decary, MSc, was published in the Healthcare Management Forum. Journal Volume 33, Issue 1 features it. The article discusses AI's rapid growth in healthcare and its promise to solve health organizations' biggest problems. It emphasizes the importance of health leaders understanding AI technologies like machine learning, natural language processing, and AI voice assistants and how they can improve healthcare efficiency, safety, and accessibility to achieve value-based care. The essay provides practical advice to help decision-makers create an AI strategy for digital healthcare transformation. Unfortunately, publication year and page numbers are not provided.
Source Summary:
The article "Artificial Intelligence (AI) in healthcare: An essential guide for health leaders" by Mei Chen, PhD and Michel Decary, MSc covers AI technologies and their potential uses in healthcare. In order to improve healthcare efficiency, safety, and accessibility, health leaders must grasp AI technologies. Health businesses confront hurdles in integrating AI, including a lack of awareness of AI capabilities, integration strategies, qualified personnel, compatibility with legacy infrastructure, and access to diverse medical data for training ML algorithms. The writers discuss machine learning, natural language processing, AI speech technology, and medical robotics and their healthcare applications. The essay advises decision-makers on AI strategies for digital healthcare transformation.
Article Title: Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications
Article Author(s): Daniel Schönberger
Retrieval Information (example website link): https://doi.org/10.1093/ijlit/eaz004
Source’s Publication Date: 2019
Publishing Information: Daniel Schönberger wrote "Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications" for the International Journal of Law and Information Technology. Volume 27, Issue 2, Summer 2019, pages 171–203.The article was Published in May 4, 2019. Schönberger examines the legal and ethical ramifications of AI's healthcare transformation in this article. The author discusses AI's uses in healthcare, its benefits, and its distinct qualities and risks. The essay examines AI technology' decision-making abilities and their ethical and legal implications. The author finds that while some areas may require sector-specific legal adjustments, the current institutions are mainly suitable to manage AI technology issues, particularly in non-discrimination and product liability.
Source Summary:
The article "Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications" by Daniel Schönberger investigates how AI may affect healthcare decision-making. AI technologies improve patient care and save expenses, yet legal and ethical issues arise. Existing frameworks can handle AI issues in healthcare, but non-discrimination and product liability may require changes. The article examines AI's effects on healthcare and stresses the necessity to consider legal and ethical issues.
References
Chen, M., & Decary, M. (2019). Artificial intelligence in healthcare: An essential guide for health leaders. Healthcare Management Forum, 33(1), 10–18. https://doi.org/10.1177/0840470419873123
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. ncbi. https://doi.org/10.7861/futurehosp.6-2-94
Schönberger, D. (2019). Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications. International Journal of Law and Information Technology, 27(2), 171–203. https://doi.org/10.1093/ijlit/eaz004
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21(1). https://doi.org/10.1186/s12911-021-01488-9
Source Evaluation | 1
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2
Project Plan
Bryan Cridell
American Military University
COMM120 – Information and Digital Literacy
Dr. Sarah Syrjanen
25 June 2023
Project Plan
Part 1
Choose a topic that is realistic and one that you want to learn more about.
The topic I have chosen is Artificial Intelligence in Healthcare, as it blends my passion for healthcare with AI's promise to improve the industry. I want to study how AI is utilized in diagnostics, treatment planning, medication discovery, and patient monitoring, as well as its benefits and drawbacks.
What is the scope of the topic and your research?
The topic "Artificial Intelligence in Healthcare" covers medical imaging, clinical decision support systems, genomics, and personalized medicine. The project will examine AI adoption in healthcare and its possible effects on patient outcomes, healthcare delivery, and the healthcare ecosystem. It will also examine AI's ethical, legal, and social effects in healthcare.
What value does it bring to your life? To your professional life?
This research holds significant value in both my personal and professional life. It will help me learn how AI may improve patient care and health outcomes. I can make better healthcare decisions for myself and my family. This research will enhance my experience in healthcare and AI. It will allow me to participate in healthcare technology conversations and advances, making me an educated and forward-thinking professional.
How are you going to communicate your project?
I will communicate my project through a PowerPoint presentation, utilizing visuals, concise text, and compelling storytelling to engage the audience.
How will you make your presentation different and unique?
Real-life case studies and examples will make my presentation stand out. I will eliminate jargon and technical complications to make the content accessible to healthcare professionals and non-experts.
Pose different questions that will help you with your research and investigate your topic in more depth.
• How can healthcare AI adoption be improved?
• How does AI affect privacy, bias, and responsibility in healthcare?
Post critical questions that will push you to improve.
• What are the hazards of using AI in healthcare, and how can they be mitigated?
• How might healthcare AI systems prioritize patient-centered treatment, considering human values, preferences, and context?
Part 2: Reflection
I will mainly use peer-reviewed published articles for my healthcare AI study. These scholarly sources are trustworthy and reviewed. I will discuss recent publications on healthcare AI applications, case studies, and empirical research. I will also look over conference proceedings and scholarly papers to learn about cutting-edge research and new trends. Healthcare associations, government entities, and research institutes will provide thorough analysis, policy recommendations, and industry viewpoints to supplement scholarly sources. I will ensure correctness, dependability, and relevance by prioritizing recent articles within the past 5-10 years, analyzing the methodology, and cross-referencing numerous sources. This method will help me create an evidence-based project plan.