Delve into the sustainable development of Artificial Intelligence and its impact on Medicine through TECH, the best digital university in the world according to Forbes"

Throughout their medical procedures, physicians access confidential patient information in order to effectively design their therapies. In this regard, their responsibilities include safeguarding user confidentiality in AI environments. Otherwise, experts could face serious consequences ranging from financial penalties to loss of their license to practice. For this reason, it is essential for specialists to develop privacy policies aimed at protecting sensitive data.

For this reason, TECH implements a Postgraduate certificate that will address in detail the integration of ethical values in AI-assisted decision making in medical contexts. The academic itinerary will delve into the guarantee of informed consent in both the collection and use of patients' personal data. Practitioners will learn multiple strategies for sustainable practices in the development and maintenance of AI systems. In this way, your procedures will comply with international data governance and regulatory frameworks. In addition, the learning materials will encourage continuous evaluation of security policies to adapt to technological advances.

All this, through didactic material based on interactive summaries of each topic, videos in detail, complementary readings and case studies to which experts will have access, comfortably, whenever and wherever they wish. Professionals taking this program only need an electronic device with an Internet connection to view, at any time of the day, the content hosted on the virtual platform. Undoubtedly, this is an ideal academic option for those seeking a first-class update through a quality program that facilitates self-management of study time.

The incorporation of ethical considerations in your daily practice, applying Machine Learning, will drive more ethical and committed medical advances"

This Postgraduate certificate in Ethics and Regulation in Medical Artificial Intelligence contains the most complete and up-to-date program on the market. The most important features include:

• The development of practical cases presented by experts in Artificial Intelligence in Clinical Practice
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

You will develop sound ethical principles to AI in Clinical Research, contributing to fairer, more transparent and socially responsible medical advances"

The program’s teaching staff includes professionals from the industry who contribute their work experience to this program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the students will be assisted by an innovative interactive video system created by renowned and experienced experts.

You will delve into the management of informed consent and responsibility in research, in the context of advanced technologies in the biomedical field"

Take advantage of all the benefits of the Relearning methodology, which will allow you to organize your time and pace of study, adapting to your schedule"

This university program will provide graduates with an in-depth knowledge of the ethical, privacy and regulatory aspects related to the implementation of AI in the healthcare environment. The curriculum will delve into the guarantee of informed consent in the collection and use of personal data in the medical field. The syllabus will also encourage professionals to ensure principles of transparency and rigor during the system validation phase. In the same vein, the learning materials will address a wide range of strategies for risk mitigation and ethical responsibility in AI applications in medicine.

Update your knowledge in the sustainable development of Artificial Intelligence through innovative multimedia content"

Module 1. Ethics and Regulation in Medical AI

1.1. Ethical Principles in the Use of AI in Medicine

1.1.1. Analysis and Adoption of Ethical Principles in the Development and Use of Medical AI Systems
1.1.2. Integration of Ethical Values in AI-assisted Decision Making in Medical Contexts
1.1.3. Establishment of Ethical Guidelines to Ensure Responsible Use of Artificial Intelligence in Medicine

1.2. Data Privacy and Consent in Medical Contexts

1.2.1. Development of Privacy Policies to Protect Sensitive Data in Medical AI Applications
1.2.2. Ensuring Informed Consent in the Collection and Use of Personal Data in Medical Settings
1.2.3. Implementing Security Measures to Safeguard Patient Privacy in Medical AI Environments

1.3. Ethics in the Research and Development of Medical AI Systems

1.3.1. Ethical Evaluation of Research Protocols in the Development of AI Health Systems
1.3.2. Ensuring Transparency and Ethical Rigor in the Development and Validation Phases of Medical AI Systems
1.3.3. Ethical Considerations in the Publication and Sharing of Results in the Field of Medical AI

1.4. Social Impact and Accountability in AI for Health

1.4.1. Analysis of the Social Impact of AI in Health Care Delivery
1.4.2. Development of Strategies to Mitigate Risks and Ethical Responsibility in AI Applications in Medicine
1.4.3. Continuous Evaluation of the Social Impact and Adaptation of AI Systems to Make a Positive Contribution to Public Health

1.5. Sustainable Development of AI in the Health Sector

1.5.1. Integration of Sustainable Practices in the Development and Maintenance of AI Systems in Health
1.5.2. Assessment of the Environmental and Economic Impact of AI Technologies in the Health Sector
1.5.3. Development of Sustainable Business Models to Ensure Continuity and Improvement of AI Solutions in Healthcare

1.6. Data Governance and International Regulatory Frameworks in Medical AI

1.6.1. Development of Governance Frameworks for Ethical and Efficient Data Management in Medical AI Applications
1.6.2. Adaptation to International Standards and Regulations to Ensure Ethical and Legal Compliance
1.6.3. Active Participation in International Initiatives to Establish Ethical Standards in the Development of Medical AI Systems

1.7. Economic Aspects of AI in the Healthcare Field

1.7.1. Analysis of Economic and Cost-Benefit Implications in the Implementation of AI Systems in Healthcare
1.7.2. Development of Business and Financing Models to Facilitate the Adoption of AI Technologies in the Healthcare Sector
1.7.3. Assessment of Economic Efficiency and Equity in Access to AI-driven Health Services

1.8. Human-centered Design of Medical AI Systems

1.8.1. Integration of Human-Centered Design Principles to Improve Usability and Acceptability of Medical AI Systems
1.8.2. Involvement of Healthcare Professionals and Patients in the Design Process to Ensure Relevance and Effectiveness of Solutions
1.8.3. Continuous Evaluation of User Experience and Feedback to Optimize Interaction with AI Systems in Medical Settings

1.9. Fairness and Transparency in Medical Machine Learning

1.9.1. Development of Medical Machine Learning Models that Promote Fairness and Transparency
1.9.2. Implementation of Practices to Mitigate Bias and Ensure Fairness in the Application of AI Algorithms in Healthcare
1.9.3. Continued Assessment of Fairness and Transparency in the Development and Deployment of Machine Learning Solutions in Medicine

1.10. Safety and Policy in the Deployment of AI in Medicine

1.10.1. Development of Security Policies to Protect Data Integrity and Confidentiality in Medical AI Applications
1.10.2. Implementation of Safety Measures in the Deployment of AI Systems to Prevent Risks and Ensure Patient Safety
1.10.3. Continuous Evaluation of Safety Policies to Adapt to Technological Advances and New Challenges in the Deployment of AI in Medicine

Make the most of this opportunity to surround yourself with expert professionals and learn from their work methodology"