HOSA Biomedical Debate 2024 Article
Questions and Answers 100% Correct
Healthcare Transformation - ANSWER-The process of fundamental change and improvement in the
healthcare industry, driven by factors such as decreasing costs, scarcity of experts, medical
technology advancements, and government regulations.
Scarcity of Educated Experts - ANSWER-The increasing shortage of knowledgeable professionals in
the healthcare industry, impacting the delivery of quality care and services.
Difficulties in Healthcare Systems - ANSWER-Challenges such as high costs and an aging population
that healthcare systems worldwide face, affecting accessibility and sustainability.
COVID-19 Impact - ANSWER-The pandemic that has stressed healthcare systems globally, revealing
flaws in accessibility, treatment availability, and cost management.
Machine Learning (ML) - ANSWER-A technique assisting medical practitioners in patient care and
clinical data management, enabling computers to learn and make decisions without explicit
programming.
Artificial Intelligence (AI) in Healthcare - ANSWER-The use of AI to decrease complexity, simplify
healthcare systems, and advance medical research, addressing various challenges and opportunities
in the industry.
Data Collection Concerns - ANSWER-Obstacles related to the gathering, storage, and utilization of
healthcare data, including privacy, security, and ethical implications.
Potential Misuse of Patient Data - ANSWER-The risk of inappropriate or unauthorized use of patient
information stored in AI-based systems, raising concerns about privacy and confidentiality.
Health Research Regulations - ANSWER-Legislation aimed at resolving data privacy issues and
ensuring ethical use of healthcare data, potentially impacting AI implementation.
, Impact of AI on patient records security - ANSWER-Predominant sentiment regarding the impact of
AI on the security of patients' health records: Deterioration
AI's role in improving data flow - ANSWER-According to Natalie Schibell, AI's role in improving data
flow involves recognizing and processing both structured and unstructured data
Quality of Data Analysis - ANSWER-The challenge of analyzing medical data for AI algorithm
development, including addressing biases and unpredictable variations in medical records.
Overfitting - ANSWER-The consequence of biases in data collection processes affecting model
development, leading to high accuracy within training data but poor generalization.
Black-box Problem - ANSWER-The lack of explanation for forecasts made by deep learning
algorithms, posing challenges in understanding and validating AI-based decisions.
Ethical Concerns in AI - ANSWER-Issues related to fairness, transparency, accountability, and societal
impact arising from the use of AI in healthcare, requiring ethical governance solutions.
Social Concerns in AI - ANSWER-Challenges such as the potential elimination of healthcare jobs and
automation of routine tasks, impacting the workforce and operations.
AI-based Medications in Clinical Trials - ANSWER-The obstacle of insufficient empirical data for
successful deployment of AI-based treatments, affecting regulatory approval and technological
development.
Integration of AI-based Treatments - ANSWER-The necessity of training medical professionals and
investing in technology for the effective incorporation of AI-based treatments into medical practice.
AI Integration in Medical Education - ANSWER-The emphasis on integrating AI across undergraduate,
postgraduate, and specialization phases of medical education to prepare professionals for AI
adoption.
AI Algorithms for Clinical Interpretation - ANSWER-The challenge of validating AI algorithms in clinical
trials, ensuring their accuracy, reliability, and regulatory compliance for clinical interpretation.
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