What will I be able to do upon completing the Specialization?

Implement benchmark pipelines for Deep Learning Algorithms with Electronic Health Records.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Informed Clinical Decision Making using Deep Learning Specialization

Informed Clinical Decision Making using Deep Learning Specialization

Apply Deep Learning in Electronic Health Records. Understand the road path from data mining of clinical databases to clinical decision support systems

Instructor: Fani Deligianni

Included with Coursera Plus

Learn more

5 course series

Get in-depth knowledge of a subject

4.6

(21 reviews)

Intermediate level

Recommended experience

2 months at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

5 course series

Get in-depth knowledge of a subject

4.6

(21 reviews)

Intermediate level

Recommended experience

2 months at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

What you'll learn

Extract and preprocess data from complex clinical databases
Apply deep learning in Electronic Health Records
Imputation of Electronic Health Records and data encodings
Explainable, fair and privacy-preserved Clinical Decision Support Systems

Overview

This specialisation is for learners with experience in programming that are interested in expanding their skills in applying deep learning in Electronic Health Records and with a focus on how to translate their models into Clinical Decision Support Systems.

The main areas that would explore are:

Data mining of Clinical Databases: Ethics, MIMIC III database, International Classification of Disease System and definition of common clinical outcomes.
Deep learning in Electronic Health Records: From descriptive analytics to predictive analytics
Explainable deep learning models for healthcare applications: What it is and why it is needed
Clinical Decision Support Systems: Generalisation, bias, ‘fairness’, clinical usefulness and privacy of artificial intelligence algorithms.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English

23 practice exercises

Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from University of Glasgow

Specialization - 5 course series

Learners have the opportunity to choose and undertake an exercise based on MIMIC-III extracted datasets that combines knowledge from:

Data mining of Clinical Databases to query the MIMIC database
Deep learning in Electronic Health Records to pre-process EHR and build deep learning models
Explainable deep learning models for healthcare to explain the models decision

Learners can choose from:

1. Permutation feature importance on the MIMIC critical care database

The technique is applied both on logistic regression and on an LSTM model. The explanations derived are global explanations of the model.

2. LIME on the MIMIC critical care database

The technique is applied on both logistic regression and an LSTM model. The explanations derived are local explanations of the model.

3. Grad-CAM on the MIMIC critical care database

GradCam is implemented and applied on an LSTM model that predicts mortality. The explanations derived are local explanations of the model.

Data mining of Clinical Databases - CDSS 1

Course 120 hours4.6 (14 ratings)View course

What you'll learn

Understand the Schema of publicly available EHR databases (MIMIC-III)
Recognise the International Classification of Diseases (ICD) use
Extract and visualise descriptive statistics from clinical databases
Understand and extract key clinical outcomes such as mortality and stay of length

Skills you'll gain

ICD Coding (ICD-9/ICD-10), Interoperability, Clinical Data Management, Predictive Analytics, SQL, Relational Databases, Clinical Informatics, Descriptive Statistics, Precision Medicine, Medical Records, Patient Flow, Exploratory Data Analysis, Analytics, Descriptive Analytics, Predictive Modeling, Health Informatics, Electronic Medical Record, Database Design, Data Mining, and Machine Learning

Deep learning in Electronic Health Records - CDSS 2

Course 231 hoursView course

What you'll learn

Train deep learning architectures such as Multi-layer perceptron, Convolutional Neural Networks and Recurrent Neural Networks for classification
Validate and compare different machine learning algorithms
Preprocess Electronic Health Records and represent them as time-series data
Imputation strategies and data encodings

Skills you'll gain

Deep Learning, Data Cleansing, Data Processing, Feature Engineering, Health Informatics, Artificial Neural Networks, Predictive Modeling, Time Series Analysis and Forecasting, Electocardiography, Electronic Medical Record, and Machine Learning Methods

Explainable deep learning models for healthcare - CDSS 3

Course 330 hours4.6 (15 ratings)View course

What you'll learn

Program global explainability methods in time-series classification
Program local explainability methods for deep learning such as CAM and GRAD-CAM
Understand axiomatic attributions for deep learning networks
Incorporate attention in Recurrent Neural Networks and visualise the attention weights

Skills you'll gain

Deep Learning, Applied Machine Learning, Time Series Analysis and Forecasting, Artificial Neural Networks, Data Processing, Machine Learning Algorithms, Machine Learning, Responsible AI, Healthcare Ethics, and Image Analysis

Clinical Decision Support Systems - CDSS 4

Course 48 hoursView course

What you'll learn

Evaluating Clinical Decision Support Systems
Bias, Calibration and Fairness in Machine Learning Models
Decision Curve Analysis and Human-Centred Clinical Decision Support Systems
Privacy concerns in Clinical Decision Support Systems

Skills you'll gain

Responsible AI, Data Ethics, Deep Learning, Predictive Modeling, Health Informatics, Artificial Intelligence and Machine Learning (AI/ML), Information Privacy, Verification And Validation, Data Security, Decision Support Systems, Human Centered Design, Machine Learning, and Data Validation

Capstone Assignment - CDSS 5

Course 52 hoursView course

What you'll learn

Skills you'll gain

Data Mining, Artificial Neural Networks, Deep Learning, Feature Engineering, Applied Machine Learning, Clinical Data Management, Responsible AI, Artificial Intelligence, Predictive Modeling, Time Series Analysis and Forecasting, Health Informatics, and Machine Learning

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Fani Deligianni

University of Glasgow

5 Courses5,921 learners

Offered by

University of Glasgow

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Frequently asked questions

Each module is designed to take 4-5 weeks. Modules two and three are heavy in practical exercise and it may take slightly longer for inexperienced in machine learning learners.

It is required basic knowledge in sql databases and how to setup a postgres database. It also requires knowledge in python programming with common scientific libraries, such as numpy, scipy and matplotlib.

Yes, the course is designed to be taken with the prespecified order. Specifically, the second module requires knowledge from the first module, the third module requires knowledge from the second module and the forth module requires high-level understanding of module one, two and three.

Informed Clinical Decision Making using Deep Learning Specialization

What you'll learn

Overview

Skills you'll gain

Tools you'll learn

What’s included

Advance your subject-matter expertise

Specialization - 5 course series

Data mining of Clinical Databases - CDSS 1

What you'll learn

Skills you'll gain

Deep learning in Electronic Health Records - CDSS 2

What you'll learn

Skills you'll gain

Explainable deep learning models for healthcare - CDSS 3

What you'll learn

Skills you'll gain

Clinical Decision Support Systems - CDSS 4

What you'll learn

Skills you'll gain

Capstone Assignment - CDSS 5

What you'll learn

Skills you'll gain

Earn a career certificate

Instructor

Offered by

Compare with similar products

You might also like

Related skills

Why people choose Coursera for their career

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

More questions

Informed Clinical Decision Making using Deep Learning Specialization

What you'll learn

Overview

Skills you'll gain

Tools you'll learn

What’s included

Advance your subject-matter expertise

Specialization - 5 course series

Data mining of Clinical Databases - CDSS 1

What you'll learn

Skills you'll gain

Deep learning in Electronic Health Records - CDSS 2

What you'll learn

Skills you'll gain

Explainable deep learning models for healthcare - CDSS 3

What you'll learn

Skills you'll gain

Clinical Decision Support Systems - CDSS 4

What you'll learn

Skills you'll gain

Capstone Assignment - CDSS 5

What you'll learn

Skills you'll gain

Earn a career certificate

Instructor

Offered by

Compare with similar products

You might also like

Related skills

Why people choose Coursera for their career

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

How long does it take to complete the Specialization?

What background knowledge is necessary?

Do I need to take the courses in a specific order?

More questions