Capstone Assignment - CDSS 5 from Coursera

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Syllabus

Permutation feature importance on the MIMIC critical care database

This is an advanced exercise/lesson that combines knowledge from the three earlier modules: 1) 'Data mining of Clinical Databases' to query the MIMIC database, 2) 'Deep learning in Electronic Health Records' to pre-process EHR and build deep learning models and 3) 'Explainable deep learning models for healthcare' to explain the models decision. In particular, permutation feature importance is implemented and applied on MIMIC-III extracted datasets. The technique is applied both on logistic regression and on an LSTM model. The explanations derived are global explanations of the model.

LIME on the MIMIC critical care database

This is an advanced exercise/lesson that combines knowledge from the three earlier modules: 1) 'Data mining of Clinical Databases' to query the MIMIC database, 2) 'Deep learning in Electronic Health Records' to pre-process EHR and build deep learning models and 3) 'Explainable deep learning models for healthcare' to explain the models decision. In particular, LIME is applied on MIMIC-III extracted datasets. The technique is applied on both logistic regression and an LSTM model . The explanations derived are local explanations of the model.

Grad-CAM on the MIMIC critical care database

This is an advanced exercise/lesson that combines knowledge from the three earlier modules: 1) 'Data mining of Clinical Databases' to query the MIMIC database, 2) 'Deep learning in Electronic Health Records' to pre-process EHR and build deep learning models and 3) 'Explainable deep learning models for healthcare' to explain the models decision. In particular, GradCam is implemented and applied on an LSTM model that predicts mortality based on MIMIC-III extracted datasets. The explanations derived are local explanations of the model.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Applies knowledge and skills learned throughout the Explainable AI in Healthcare specialization

Covers specialized techniques like permutation feature importance, LIME, and Grad-CAM for explainable deep learning models in healthcare

Provides hands-on labs for applying these techniques on the MIMIC critical care database

Assumes prior knowledge in data mining of clinical databases, deep learning in electronic health records, and explainable deep learning models for healthcare

Activities

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Brush up on programming skills in Python

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Ensure you have a strong foundation in Python, the primary programming language used in the course.

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Review Python syntax, data structures, and control flow.
Practice writing simple Python scripts and functions.

Review basic machine learning concepts

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Help you recall and strengthen your foundational knowledge of machine learning, making it easier to grasp the advanced concepts covered in the course.

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Revisit key concepts such as supervised and unsupervised learning, feature extraction, and model evaluation.
Review resources such as textbooks, online tutorials, or lecture notes to refresh your understanding.

Practice building and evaluating simple machine learning models

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Provide you with hands-on experience in applying machine learning techniques, reinforcing your understanding and improving your problem-solving skills.

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Choose a dataset and define the problem you want to solve.
Preprocess the data, select features, and train a simple model.
Evaluate the model's performance using appropriate metrics.
Repeat the process with different models and parameters to compare their performance.

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Engage in discussion forums and collaborate with peers

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Foster collaboration and knowledge sharing, allowing you to learn from others' perspectives and gain new insights.

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Actively participate in discussion forums related to the course material.
Ask questions, share your thoughts, and engage with other students.
Collaborate on projects or assignments to leverage diverse skills and perspectives.

Explore online tutorials on advanced deep learning techniques

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Expose you to cutting-edge deep learning techniques, expanding your knowledge and keeping you up-to-date with the latest advancements.

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Identify reputable online platforms or courses that offer tutorials on advanced deep learning topics.
Choose a specific technique or model that interests you.
Follow the tutorials, complete exercises, and ask questions in discussion forums.
Implement the techniques in your own projects or assignments.

Create a short presentation on a machine learning algorithm

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Challenge you to synthesize your knowledge and communicate it effectively, enhancing your understanding and presentation abilities.

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Choose a specific machine learning algorithm and research its details.
Create a presentation outline and gather relevant information.
Design slides that clearly explain the algorithm's concepts and applications.
Practice delivering your presentation and gather feedback for improvement.

Contribute to an open-source project related to machine learning

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Provide you with real-world experience in machine learning, contribute to the community, and enhance your problem-solving skills.

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Identify an open-source project that aligns with your interests and skills.
Familiarize yourself with the project's codebase and documentation.
Identify an area where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
Create a pull request with your changes and actively participate in the review process.

Career center

Learners who complete Capstone Assignment - CDSS 5 will develop knowledge and skills that may be useful to these careers:

Health Data Analyst

The Health Data Analyst plays a crucial role in analyzing and interpreting large datasets relevant to healthcare. This course provides a strong foundation in data mining, deep learning, and explainable AI, which are essential skills for extracting meaningful insights. By understanding the techniques covered in this course, you can enhance your ability to process and analyze healthcare data to inform decision-making and improve patient outcomes.

See salaries and explore the career path for Health Data Analyst

Machine Learning Engineer

Machine Learning Engineers leverage technical expertise to design, implement, and maintain machine learning models. This course equips you with the necessary knowledge in deep learning and explainable AI, which are crucial for developing and deploying effective AI solutions in healthcare. By completing this course, you gain a competitive edge in the field and can contribute to advancements in patient care.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists specialize in extracting knowledge from data and applying it to solve real-world problems. This course provides a comprehensive understanding of data mining, deep learning, and explainable AI, which are essential tools for data scientists working in healthcare. By mastering these techniques, you can effectively analyze healthcare data, identify patterns, and develop data-driven solutions to improve patient outcomes.

See salaries and explore the career path for Data Scientist

Medical Informatics Specialist

Medical Informatics Specialists bridge the gap between healthcare and technology. This course provides a comprehensive understanding of data mining, deep learning, and explainable AI, which are essential skills for developing and implementing innovative healthcare solutions. By mastering these techniques, you can contribute to the advancement of medical informatics and improve patient care.

See salaries and explore the career path for Medical Informatics Specialist

Biostatistician

Biostatisticians apply statistical methods to analyze and interpret data in healthcare and biomedical research. This course provides a strong foundation in data mining, deep learning, and explainable AI, which are increasingly used in biostatistics. By completing this course, you can enhance your ability to analyze complex healthcare data and contribute to the development of evidence-based healthcare practices.

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Research Scientist

Research Scientists conduct scientific research and develop new technologies. This course provides a solid foundation in data mining, deep learning, and explainable AI, which are essential for conducting cutting-edge research in healthcare and biomedical sciences. By completing this course, you can enhance your ability to design and execute research projects, contribute to scientific knowledge, and advance patient care.

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Healthcare Consultant

Healthcare Consultants provide expert advice and guidance to healthcare organizations. This course enhances your understanding of data mining, deep learning, and explainable AI, which are increasingly used in healthcare settings. By completing this course, you can develop a deeper understanding of the data-driven aspects of healthcare, enabling you to provide more informed and effective consulting services.

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Clinical Research Associate

Clinical Research Associates play a vital role in the development and execution of clinical trials. This course provides a solid foundation in data mining, deep learning, and explainable AI, which can enhance your ability to analyze clinical data, assess patient outcomes, and ensure the integrity of research findings. By taking this course, you can gain a competitive advantage in the field and contribute to the advancement of medical knowledge.

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Clinical Data Manager

Clinical Data Managers oversee the collection, management, and analysis of clinical data. This course provides a comprehensive understanding of data mining, deep learning, and explainable AI, which are becoming increasingly important in clinical data management. By completing this course, you can enhance your ability to manage and analyze clinical data effectively, ensuring its accuracy and integrity.

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Health Economist

Health Economists analyze the cost-effectiveness and value of healthcare interventions. This course provides a comprehensive understanding of data mining, deep learning, and explainable AI, which are increasingly used in health economics. By completing this course, you can enhance your ability to evaluate the economic impact of healthcare decisions and contribute to more efficient and equitable healthcare systems.

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Healthcare Policy Analyst

Healthcare Policy Analysts develop and evaluate policies that affect healthcare systems and patient care. This course provides a comprehensive understanding of data mining, deep learning, and explainable AI, which are increasingly used in healthcare policy analysis. By completing this course, you can enhance your ability to analyze healthcare data, assess the impact of policies, and contribute to the development of more effective healthcare policies.

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Epidemiologist

Epidemiologists investigate the causes and patterns of health-related events. This course provides a strong foundation in data mining, deep learning, and explainable AI, which are becoming increasingly important in epidemiology. By completing this course, you can enhance your ability to analyze health data, identify risk factors, and develop evidence-based public health interventions.

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Pharmacist

Pharmacists provide medication-related advice and services to patients. This course may be useful for Pharmacists seeking to enhance their understanding of data mining, deep learning, and explainable AI, which are increasingly used in drug development and personalized medicine. By completing this course, you can gain a competitive edge in the field and contribute to improved patient outcomes.

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Nurse

Nurses provide direct patient care and play a vital role in healthcare delivery. This course may be useful for Nurses seeking to enhance their understanding of data mining, deep learning, and explainable AI, which are increasingly used in healthcare settings. By completing this course, you can gain a better understanding of data-driven approaches to patient care and contribute to improved patient outcomes.

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Healthcare Administrator

Healthcare Administrators oversee the management and operation of healthcare organizations. This course may be useful for Healthcare Administrators seeking to enhance their understanding of data mining, deep learning, and explainable AI, which are becoming increasingly important in healthcare administration. By completing this course, you can gain a competitive edge in the field and contribute to more efficient and effective healthcare organizations.

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Capstone Assignment - CDSS 5

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