Data science for clinicians: Introduction to coding and data visualization

This course has been created to introduce clinicians to data science and provide them with basic skills to handle data. The course aims to encourage clinicians to work confidently and effectively with their data.

Course Overview

Clinicians are confronted with data every day but often do not have the means or understanding of handling this data correctly. This course will provide delegates with hands on learning experience using tools and knowledge to make correct decisions in handling data, which will result in better quality of clinical research.

With Moorfields and the UCL Institute of Ophthalmology being at the forefront of clinical research, you will be learning from world class clinicians with data science experience who will provide insights into real life clinical data from authentic clinical perspectives.

A further course - Data science for clinicians: Intensive course in R - is available for those wishing to further develop their skills on completion of this course. Please see the course fees section of this page for details of the discount available if both courses are purchased together.

Course Structure

This is a self-paced course that will be delivered online over two days. You will work through five course sections. There will be an opportunity to ask questions via a Q&A session. The course sections are as follows:

1. Introduction to data science

This course section will explore the following questions and topics:

  • What is clinical data?
  • Why should clinicians understand data science?
  • Data and telemedicine
  • How will data transform clinical practice?
  • What is a data base?

2. Coding and computer languages

This course section will give an overview about coding and computer languages and explore why coding can be useful in times of excel.

  • Introduction to coding / computer languages
  • Which computer language to choose?
  • Overview over most commonly used computer languages
  • Useful online resources and how to use them

 3. Common statistical tests and challenges with clinical data

This section explores commonly used statistical tests and models in clinical data. Although some of the basics will be repeated, this course section does not intend to replace a statistical course and therefore requires some basic statistical knowledge. 

4. Commonly encountered errors/ misconceptions in statistics

Going further, this course section will explore commonly encountered errors in statistical testing in a clinical setting. This course section also requires basic statistical knowledge. 

5. Principles of data visualisation

This course section will explore the principles of good data visualisation, in particular the pillars Graphical excellence, Graphical integrity, Graphical sophistication and Graphical elegance. Further, commonly encountered visualisation “errors" or “sins” will be presented. This course will not show the technical details how to create the visualisation. If you want to learn how to produce high quality graphs with the computer language R, we recommend to take the course Data science for clinicians: Intensive course in R.

Who should apply

This course is intended for junior doctors and allied health professionals (including nurses, optometrists, health technicians) who work clinically and are keen to learn how to use data for academic work, particularly involving Big Data and Artificial Intelligence. It is also suitable for researchers and students undertaking scientific & medical research.

Requirement

In order to access the programme online, you will need access to a computer (laptop or desktop) with a webcam and microphone.

Book Now

Date Location Time Seats Price
10/05/2021 - 11/05/2021 Online 9:00 AM (GMT) 9 £350.00
 

Course fees

 

Taught by

 

Tjebo Heeren

Dr Heeren is an Ophthalmologist with specialist interest in Medical Retina. He has a particular research interest in Macular Telangiectasia type II and has pioneered image analysis methods that offered new insight into the understanding of this rare disease. Dr Heeren is involved in a number of imaging, clinical and basic science research projects pertaining to MacTel.

Konstantinos Balaskas

Consultant Ophthalmologist and Director of the Moorfields Ophthalmic Reading Centre (since November 2017): Since taking up the role of Director of the Moorfields Reading centre, I have been working to establish the Reading Centre as a pioneer in the Big Data and Artificial Intelligence ecosystem through academic and commercial collaborations, including with Google DeepMind. Novel, efficient methods of image grading are being developed through the AI pipeline allowing faster turn-around and enabling exploratory projects on novel biomarkers of response to treatment for retinal disease. Service Delivery Research and Implementation Science: I have a keen interest in new ways of delivering care in Ophthalmology, including with tele-medicine, ‘virtual’ clinics and Artificial Intelligence. I have led two national research projects in the UK funded by the National Institute of Health Research looking at novel care models for Ophthalmology patients, exploring the role of modern imaging and digital technologies. I am developing the role of the Reading Centre as a tele-ophthalmology hub in the context of novel models of care, including ‘virtual clinics’, AI and home-monitoring. Principal Investigator for Clinical Trials: I have received national recognition as one of the Best Principal Investigators for Clinical Trials in the UK for three consecutive years. This has equipped me with in-depth understanding of the challenges of research governance and clinical trial set-up and monitoring. I am bringing this knowledge and expertise into my current role as Director of the Moorfields Reading Centre.