Medical statistics, informatics and telemedicine 2021-2022
Leírás
Általános információk
3rd year 1 semester
Lecture 1 hour/week
Practice 1 hour/week
Conditions for signature: Participation on at least 75 % of the practices, (in case of more than 3 absences the signature for the semester is denied.)
Semifinal exam: Written test. On the basis of the test the grade can be between 1 and 4. Those, who achieve 4 can continue with additional, this time calculation questions for the grade 5, but in this case the grade 4 is aready guaranteed.
Requirements can be downloaded here
Actual information on the moodle:
Moodle link
ATTENTION! The lectures, exercises, exam tabs are not updated regularly, not all study materials, extra materials, etc. are available in this page! Please use the Moodle instead!
A tantárgy rövid leírása
In recent years, medicine relies more intensively on statistics, as well as on the use and interactive management of databases. Our aim is to introduce students to the fundamentals of data analysis and decision support methods that are most common in medical practice.
The subject focuses on the presentation of basic principles and concepts. We focus on logical thinking rather than computational techniques. The aim of the exercises is to deepen the knowledge conveyed in the lectures in a problem-oriented way and to apply it realistically. The calculation tasks that occasionally occur in the exercises are performed using simple, easy-to-use software on specified databases. During the internships, students have to acquire knowledge on making basic descriptive figures and tables, as well as interpret scientific publications results.
Előadások
Előadások
| 1 | Principles of quantitative medicine. (Kellermayer Miklós) | 2021.09.10. | Intro_Med_Statistics_20210910_1.pdf |
| 2 | Base concept of descriptive statistics. (Veres Dániel Sándor) | 2021.09.17. | descriptive_stat_20210917_slides.pdf |
| 3 | Event, probability, distribution. (Schay Gusztáv) | 2021.09.24. | esemeny_valoszinuseg_eloszlas_schg_EN.pdf |
| 4 | Estimations. (Agócs Gergely) | 2021.10.01. | Stat21_04_EN_presentation.pdf |
| 5 | Hypothesis testing in medical practice. (Agócs Gergely) | 2021.10.08. | Stat21_05_EN_presentation.pdf |
| 6 | T-tests, chi-square tests. Multiple comparisons. (Schay Gusztáv) | 2021.10.15. | t_chi2_tobbszoros_EN.pdf |
| 7 | Correlation. Linear regression. (Agócs Gergely) | 2021.10.22. | Stat21_07_EN.pdf |
| 8 | Argumentations. Biases. (Agócs Gergely) | 2021.10.29. | stat_21EN_08.pdf |
| 9 | Confounding and multiple linear regression. (Veres Dániel Sándor) | 2021.11.05. | conf_mlinreg_jegyzetekkel.pdf |
| 10 | Evaluation of diagnostic tests. (Kaposi András) | 2021.11.12. | 2021-11-12_Evaluation_of_diagnostic_tests_KAD.pdf ROC_eng.xlsx |
| 11 | Base statistical concepts in epidemiology. Epidemiological measures. ROC curves. Likelihood-ratios. (Veres Dániel Sándor) | 2021.11.19. | lecture11_epid_roc_LR.pdf |
| 12 | Dialogue with statistician. Survey. 3 is enough? "Nice" datatables. "Not too bad" survey. (Veres Dániel Sándor) | 2021.11.26. | ea12_kerdoiv_statisztikussal_vds_eng_v4.pdf |
| 13 | Bayesian methods. (Schay Gusztáv) | 2021.12.03. | Bayes_EN.pdf |
| 14 | Information theory, databases, expert systems. (Schay Gusztáv) | 2021.12.10. | informacioelmelet_adatbazis_schg_EN.pdf |
Gyakorlatok
Gyakorlatok
| 1 | framingham allfactor dataset | frmgham2_paired13_allfactor_empty_long2.xls frmgham2_period3_allfactor_empty.xls p12_all_in_one.xlsx Dataset13.xlsx sleep2.xlsx |
Vizsga
Vizsga
We organize consultations in the exam period.
Please register in the moodle if you willing to come.