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DDH
General
Module A (0/4) - intro to biomedical informatics and health information systems
Module A (1/4) - Relational databases
Module A (2/4) - Biomedical ontologies and terminologies
Module A (3/4) - Electronic health data capture
Module A (4/4) - Data models, standards and interoperability
Module A (Final live) - merge it all together and wrap-up of Module A
Statistics Textbook
Module B (1/6) - Lect 1 Descriptive Graphical Analysis
Module B (2/6) - Lect 2 Describing Numerical Data
Exercise Excel on descriptive statistics #1-Due by 6th of May
Exercise Excel on descriptive statistics #2-Due by 6th of May
Module B (3/6) - Lect 3 Inferential Theory
Exercise Excel on inferential statistics #3-Due by 6th of May
LIve lecture 1 - Mod B
Rules for the final exam
Module B (4/6) - Lect 4 Hypothesis Test_I
Module B (5/6) - Lect 4 Hypothesis Test_II
Module B (6/6) - Lect 4 Contingency Tables Analysis
Live Lecture 2 - Mod B
Final exam Dataset
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Final exam Dataset
Paper describing another data set from Enea Parimbelli
Paper describing another data set from Enea Parimbelli
Click
Parimbelli_dataset.pdf
link to view the file.
◄ Data set for the final exam
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Data driven healthcare student forum
util
ultrasound report example
Assignment 1 - Design normalized database tables
Assignment 2 - Use ER diagram to design a relational DB
Assignment 3 - read two review papers on ICD-9/10 and SNOMED
Assignment 4 - Find your way around a SNOMED browser and retrieve some codes
Assignment 5 - Read about REDCap and a bit of its history
Assignment 6 - Try using REDCap yourself!
Assignment 7 - explore the FHIR official documentation and look at a concrete example of FHIR profiles developed for a research use-case
Newbold textbook
Graphical analysis
Mod_B_Lecture_1_part_1
Mod_B_Lecture_1_part_2
Mod_B_Lecture_1_part_3
Describing Numerical Data
Mod_B_Lecture_2_part_1
Mod_B_Lecture_2_part_2
Exercise descriptive statistics #1
Exercise descriptive statistics #2
Inferential Theory
Mod_B_Lecture_3_part_a
Mod_B_Lecture_3_part_b
Point and interval estimate exercise
Measures for categorical data
Python Live Lecture 1
Recorded Live lecture 1
general rules
Lect 4 Hypothesis Test_I
Mod_B_Lecture_4_part_a
Mod_B_Lecture_4_part_b
Lect 4 Hypothesis Test_II
Mod_B_Lecture_4bis
Contingency Tables Analysis
Mod B Lecture 5
Anova Analysis
Python script
Live Lecture 2
Data set for the final exam