Thanks to this 100% online Postgraduate certificate, you will be able to contribute to the advancement of Medicine, applying innovative Artificial Intelligence solutions in the diagnosis of various pathologies”

Advanced applications of Artificial Intelligence in medical imaging are transforming the diagnosis and treatment of pathologies, from the early detection of Cancer with convolutional neural networks, to the identification of neurodegenerative diseases through the analysis of complex patterns in MRI and CT scans.  In addition, AI makes it possible to prioritize critical cases in radiology, improve tumor segmentation, optimize image quality and predict the evolution of diseases. 

In this sense, the academic itinerary contains an integral approach, thanks to which doctors will strengthen their knowledge in the design and execution of observational studies, applying Artificial Intelligence for the selection of populations, the control of variables and long-term follow-up. In addition, the validation and calibration of models will be studied, with tools such as Arterys Cardio AI, ensuring the accuracy of predictions in various clinical conditions.

During this program, professionals will also master methods of integrating medical imaging data with other biomedical sources, optimizing diagnoses through the fusion of clinical, genetic and laboratory information. Likewise, they will approach multidisciplinary use cases, applying deep learning algorithms specific to medical imaging and understanding the importance of interdisciplinary collaboration in advanced research. Finally, the syllabus will cover simulations and computational modeling for diagnostic imaging, highlighting the use of Virtual and Augmented Reality for image-guided surgical procedures.

In this way, this 100% online Postgraduate certificate offers graduates the flexibility to take it in a comfortable way, in the place and time of their choice, only needing an electronic device with Internet access.  It is a modality adapted to current needs, which guarantees to position students in a high demand sector, thanks to the revolutionary Relearning methodology, consisting in the repetition of key concepts for an optimal and organic assimilation of the contents.

You will delve into the most advanced techniques in medical image analysis with the help of Artificial Intelligence, thanks to an extensive library of innovative multimedia resources”

This Postgraduate certificate in Advanced Applications of Artificial Intelligence in Medical Imaging Studies and Analysis contains the most complete and up-to-date scientific program on the market. The most important features include:

• The development of practical cases presented by experts in Artificial Intelligence applied to Diagnostic Imaging
• The graphic, schematic and eminently practical contents with which it is conceived gather scientific and practical information on those disciplines that are indispensable 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

With the Relearning methodology, healthcare professionals will combine the study of clinical cases with a learning system based on the continuous reiteration of key concepts”

The program's teaching staff includes professionals from the sector who bring to this program the experience of their work, in addition to recognized specialists from prestigious reference societies and 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 course. For this purpose, students will be assisted by an innovative interactive video system created by renowned and experienced experts.

You will cover topics such as image segmentation and classification, pathology detection, predictive model generation and the development of AI-assisted tools"

Become an expert in Artificial Intelligence and Medical Image Analysis by taking this Postgraduate certificate from anywhere in the world and at any time of the day. What are you waiting for to enroll?"

This Postgraduate certificate will include an introduction to fundamental concepts of Artificial Intelligence and machine learning, with a particular focus on Convolutional Neural Networks (CNN) and their application in detection, segmentation and classification of medical images. In addition, image processing techniques, AI-assisted diagnosis and the use of advanced Deep Learning tools will be analyzed. In this way, professionals will acquire practical skills through the use of specialized software, preparing them to face the current challenges in the field of automated medical analysis.

Get up to date on the latest developments offered by Artificial Intelligence in the area of Medicine, thanks to this comprehensive syllabus validated by the best digital university in the world, according to Forbes: TECH”

Module 1. Advanced Applications of Artificial Intelligence in Medical Imaging Studies and Analysis

1.1.  Design and Execution of Observational Studies using Artificial Intelligence in Medical Imaging with Flatiron Health

1.1.1. Criteria for the Selection of Populations in Artificial Intelligence Observational Studies
1.1.2. Methods for Controlling Confounding Variables in Imaging Studies
1.1.3. Strategies for Long-Term Follow-Up in Observational Studies
1.1.4. Analysis of Results and Validation of Artificial Intelligence Models in Real Clinical Settings

1.2. Validation and Calibration of AI Models in Image Interpretation with Arterys Cardio AI

1.2.1. Cross-Validation Techniques Applied to Diagnostic Imaging Models
1.2.2. Methods for Probability Calibration in AI Predictions
1.2.3. Performance Standards and Accuracy Metrics for AI Evaluation
1.2.4. Implementation of Robustness Testing in Different Populations and Conditions

1.3. Methods of Integrating Imaging Data with other Biomedical Sources

1.3.1. Data Fusion Techniques to Improve Image Interpretation
1.3.2. Joint Analysis of Images and Genomic Data for Accurate Diagnoses
1.3.3. Integration of Clinical and Laboratory Information in Artificial Intelligence Systems
1.3.4. Development of User Interfaces for Integrated Visualization of Multidisciplinary Data

1.4. Use of Medical Imaging Data in Multidisciplinary Research with Enlitic Curie

1.4.1. Interdisciplinary Collaboration for Advanced Image Analysis
1.4.2. Application of Artificial Intelligence Techniques from other Fields in Diagnostic Imaging
1.4.3. Challenges and Solutions in the Management of Large and Heterogeneous Data
1.4.4. Case Studies of Successful Multidisciplinary Applications

1.5. Specific Deep Learning Algorithms for Medical Imaging with Aidoc

1.5.1. Development of Image-Specific Neural Network Architectures
1.5.2. Optimization of Hyperparameters for Medical Imaging Models
1.5.3. Transfer of Learning and its Applicability in Radiology

1.6. Challenges in the Interpretation and Visualization of Features Learned by Deep Models

1.6.1. Optimization of the Interpretation of Medical Images by Automation with Viz.ai
1.6.2. Automation of Diagnostic Routines for Operational Efficiency
1.6.3. Early Warning Systems for Anomaly Detection
1.6.4. Reduction of Radiologists' Workload by Means of Artificial Intelligence Tools
1.6.5. Impact of Automation on the Accuracy and Speed of Diagnostics

1.7. Simulation and Computational Modeling in Diagnostic Imaging

1.7.1. Simulations for Training and Validation of Artificial Intelligence Algorithms
1.7.2. Modeling of Diseases and their Representation in Synthetic Images
1.7.3. Use of Simulations for Treatment and Surgery Planning
1.7.4. Advances in Computational Techniques for Real-Time Image Processing

1.8. Virtual and Augmented Reality in Medical Image Visualization and Analysis

1.8.1. Virtual Reality Applications for Diagnostic Imaging Education
1.8.2. Use of Augmented Reality in Image-Guided Surgical Procedures
1.8.3. Advanced Visualization Tools for Therapeutic Planning
1.8.4. Development of Immersive Interfaces for the Review of Radiological Studies

1.9. Data Mining Tools Applied to Diagnostic Imaging with Radiomics

1.9.1. Techniques for Data Mining of Large Medical Image Repositories
1.9.2. Pattern Analysis Applications for Image Data Collections
1.9.3. Biomarker Identification through Image Data Mining
1.9.4. Integration of Data Mining and Machine Learning for Clinical Discovery

1.10. Development and Validation of Biomarkers using Image Analysis with Oncimmune

1.10.1. Strategies to Identify Imaging Biomarkers in Various Diseases
1.10.2. Clinical Validation of Imaging Biomarkers for Diagnostic Use
1.10.3. Impact of Imaging Biomarkers on Treatment Personalization
1.10.4. Emerging Technologies in the Detection and Analysis of Biomarkers through Artificial Intelligence

Make the most of this opportunity to learn about the latest advances in this subject to apply it to your daily practice"