AI Healthcare and Bioethics: Patient Privacy and Data Security PDF

AI Healthcare and Bioethics: Patient Privacy and Data Security Tiana Silverio, Joey Schalip, Cole Mascari, Grayson Clark, Dominic Fazzone  AI technologies are increasingly used to analyze medical data, assist in diagnosis, and P...

AI Healthcare and Bioethics: Patient Privacy and Data Security Tiana Silverio, Joey Schalip, Cole Mascari, Grayson Clark, Dominic Fazzone  AI technologies are increasingly used to analyze medical data, assist in diagnosis, and Patient Privacy and personalize treatments. While Data Security these advances offer tremendous benefits, they also introduce ethical challenges, especially concerning patient privacy.  Data Collection and Consent: A significant bioethical concern is AI systems require large datasets whether patients fully understand to function effectively, often how their data is being used. derived from electronic health Informed consent is critical, yet records (EHRs), genetic data, and patients may not always be aware even real-time health monitoring of the full extent to which AI devices. systems analyze their health data.  AI technologies are transforming healthcare by Potential enabling more precise analysis of medical data, supporting accurate diagnoses, and Benefits of AI personalizing treatment plans. Healthcare These advancements improve patient outcomes, streamline clinical workflows, and enable earlier disease detection through predictive analytics.  Security Risks of AI The reliance on large datasets With the potential misuse of for AI in healthcare raises sensitive patient data and the concerns about data absence of standardized breaches and unauthorized protocols for data sharing and access, with past incidents encryption, healthcare highlighting vulnerabilities in professionals face ethical and cybersecurity legal challenges.  AI can quickly analyze imaging data, identify patterns in large datasets, and tailor treatment options to individual patient profiles, potentially enhancing the overall quality of care. Example: This can lead to developing personalized medicine strategies Helpful AI that target an individual's unique genetic makeup. Effective treatments with fewer side effects, especially for conditions like cancer, where therapies can be designed to attack only cancerous cells based on a patient's genetic profile  Many hospitals use AI systems to manage and analyze EHRs, improving patient care through data-driven insights. However, EHR systems are common targets for cyberattacks. Example: In 2020, a major data breach at Universal Electronic Health Services (UHS) led to compromised EHR systems across multiple hospitals, Healthcare affecting millions of patient records. Records (EHR) AI systems that store and process these records are vulnerable to hacking, potentially exposing sensitive patient information. Quiz Questions