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November 26, 2024
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This course is part of Informed Clinical Decision Making using Deep Learning Specialization
Instructor: Fani Deligianni
2,897 already enrolled
Included with
(13 reviews)
Recommended experience
Intermediate level
Basic background in sql/postgres queries is required along with knowledge in python programming and packages such as numpy, scipy and matplotlib.
(13 reviews)
Recommended experience
Intermediate level
Basic background in sql/postgres queries is required along with knowledge in python programming and packages such as numpy, scipy and matplotlib.
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
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This course will introduce MIMIC-III, which is the largest publicly Electronic Health Record (EHR) database available to benchmark machine learning algorithms. In particular, you will learn about the design of this relational database, what tools are available to query, extract and visualise descriptive analytics.
The schema and International Classification of Diseases coding is important to understand how to map research questions to data and how to extract key clinical outcomes in order to develop clinically useful machine learning algorithms.
This module will introduce MIMIC-III, which is the largest publicly Electronic Health Record (EHR) database available to benchmark machine learning algorithms. In particular, you will learn about the design of this relational database, what tools are available to query, extract and visualise descriptive analytics. The schema and International Classification of Diseases coding is important to understand how to map research questions to data and how to extract key clinical outcomes in order to develop clinically useful machine learning algorithms.
6 videos9 readings1 assignment2 discussion prompts
This week includes a discussion of the basic structure of MIMIC III database and practical exercises on how to extract and visualise summary statistics. We will understand the difficulty in defining clinical outcomes and we are going to examine clinical variables related to a specific patient.
5 videos7 readings1 assignment1 discussion prompt
This week discusses the history of the International Classification of Diseases (ICD) system, which has been developed collaboratively so that the medical terms and information in death certificates can be grouped together for statistical purposes. Practical examples shows how to extract ICD-9 codes from MIMIC III database and visualise them. Furthermore, we discuss differences between ICD-9, ICD-10 and ICD-11 systems.
5 videos6 readings1 assignment1 discussion prompt
This week includes an overview of clinical concepts, which are statistical tools to provide illness scores. They are developed based on expert opinion and subsequently extended based on data-driven methods. These models are the precursor of machine learning models for precision medicine. Finally, the practical exercises of this week provides the opportunity to implement a complex flowchart of patients inclusion.
3 videos11 readings2 assignments1 discussion prompt
The University of Glasgow has been changing the world since 1451. It is a world top 100 university (THE, QS) with one of the largest research bases in the UK. We are a member of the prestigious Russell Group of leading UK Universities with annual research income of more than £179m. The University’s #TeamUofG community is truly international with over 8000 staff and 28,0000 students from more than 140 countries. A 2019 Time Out survey placed Glasgow in the top ten cities in the world. Ranked between Berlin and Paris, Glasgow was voted number one for both friendliness and affordability. Right now our dedicated community of staff, students and alumni is working to address the challenges of Covid-19 and understand how we can make life safer for everyone.
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Reviewed on Aug 2, 2022
This course is highly informative and practical-oriented. It has increased my desire in the clinical data analytics field
Reviewed on Jul 19, 2023
This is a great learning curve to properly introduce me into data analysis, and machine learning in healthcare data
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