AI Healthcare and Bioethics: Patient Privacy and Data Security Presentation PDF

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

AI Healthcare and Bioethics: Patient Privacy and Data Security Tiana Silverio, Joey Schalip, Cole Mascari, Grayson Clark, Dominic Fazzone Patient Privacy AI technologies are increasingly and Data used to analyze medical data, Security assist in diagnosis, and personalize treatments. While (definition) these advances offer tremendous benefits, they also introduce ethical challenges, especially concerning patient privacy. Data Collection and Consent: A significant bioethical AI systems require large concern is whether patients datasets to function fully understand how their effectively, often derived data is being used. Informed from electronic health consent is critical, yet records (EHRs), genetic data, patients may not always be and even real-time health aware of the full extent to monitoring devices. which AI systems analyze their health data.  Potential AI technologies are transforming healthcare by Benefits of enabling more precise analysis of medical data, supporting accurate diagnoses, and AI personalizing treatment plans. Healthcare These advancements improve patient outcomes, streamline clinical workflows, and enable earlier disease detection through predictive analytics. How AI can be a security risk The reliance on large datasets for AI in With the potential misuse healthcare raises of sensitive patient data concerns about data and the absence of breaches and standardized protocols unauthorized access, with for data sharing and past incidents encryption, healthcare highlighting professionals face ethical vulnerabilities in and legal challenges. cybersecurity  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. This can lead to developing Example: 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, affecting Healthcare 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