Health informatics
A.A. 2019/2020
Obiettivi formativi
The course is divided in three modules.
The first module deals with the use of standardized medical search tools, health websites, online social media/networks, and mobile health tools (apps for smartphone and tablets) for medical updating and practice. The purpose of this module is to introduce the student on the emerging web 2.0 and social media technologies and how they are applied to the medical field. In addition, an overview of the use of ICT in medicine will be provided.
The second module deals with Bioinformatics. The purpose of this module is to introduce the student to the complex research area of genomics and high-throughput experiments, which is revolutionising many areas of research in Medicine, from drug discovery to personalized medicine. Biology has become the land of the "-omics", including genomics, transcriptomics, proteomics, lipidomics, metabolomics, etc. Each of these "-omics" generates a huge amount of high throughput data, and it is a challenge both to analyze these data and to further investigate the function of specific molecules.
The first module deals with the use of standardized medical search tools, health websites, online social media/networks, and mobile health tools (apps for smartphone and tablets) for medical updating and practice. The purpose of this module is to introduce the student on the emerging web 2.0 and social media technologies and how they are applied to the medical field. In addition, an overview of the use of ICT in medicine will be provided.
The second module deals with Bioinformatics. The purpose of this module is to introduce the student to the complex research area of genomics and high-throughput experiments, which is revolutionising many areas of research in Medicine, from drug discovery to personalized medicine. Biology has become the land of the "-omics", including genomics, transcriptomics, proteomics, lipidomics, metabolomics, etc. Each of these "-omics" generates a huge amount of high throughput data, and it is a challenge both to analyze these data and to further investigate the function of specific molecules.
Risultati apprendimento attesi
At the end of the first module the student will be able to perform a search in medical databases through mesh terms and advanced features and will know web 2.0 and social media technologies.
At the end of the second module the student will know how artificial intelligence will shape and change medicine in future and will be able to distinguish between real possibilities from media announcements.
At the end of the third module the student will be able to use Excel for statistical calculations and for performing multiple testing corrections typical of Bioinformatics applications. The student will have a general understanding of the challenges and opportunities coming from high-throughput experiments.
At the end of the second module the student will know how artificial intelligence will shape and change medicine in future and will be able to distinguish between real possibilities from media announcements.
At the end of the third module the student will be able to use Excel for statistical calculations and for performing multiple testing corrections typical of Bioinformatics applications. The student will have a general understanding of the challenges and opportunities coming from high-throughput experiments.
Periodo: Secondo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Edizione unica
Responsabile
Programma
MODULE 1: INTERNET, SOCIAL MEDIA AND HEALTH APPS IN MEDICINE
Lecture 1. How to use PubMed. Medline and PubMed: an introduction. Exercise on how to use Medline.
Lecture 2. How to use Internet and other databases for medical updating and practice. Exercise on how to use databases for medical updating and practice.
Lecture 3. How to use social media for medical updating and practice. Exercise on how to use social media for medical updating and practice
Lecture 4. Digital health. Mobile health, telemedicine and ehealth.
Lecture 5. Digital therapeutics. What they are, what they are not, how they are developed, how to study them, how to regulate them.
MODULE 2: ARTIFICIAL INTELLIGENCE IN MEDICINE
Lecture 1: Big Data in the health sector:
MODULE 3: BIOINFORMATICS
Lecture 1. Using a Computer for Clinical Data Presentation
Lecture 2. Introduction to Statistical Calculators (Statpages and Quick-calcs)
Lecture 3. Multiple testing: problems and solutions
Lecture 1. How to use PubMed. Medline and PubMed: an introduction. Exercise on how to use Medline.
Lecture 2. How to use Internet and other databases for medical updating and practice. Exercise on how to use databases for medical updating and practice.
Lecture 3. How to use social media for medical updating and practice. Exercise on how to use social media for medical updating and practice
Lecture 4. Digital health. Mobile health, telemedicine and ehealth.
Lecture 5. Digital therapeutics. What they are, what they are not, how they are developed, how to study them, how to regulate them.
MODULE 2: ARTIFICIAL INTELLIGENCE IN MEDICINE
Lecture 1: Big Data in the health sector:
MODULE 3: BIOINFORMATICS
Lecture 1. Using a Computer for Clinical Data Presentation
Lecture 2. Introduction to Statistical Calculators (Statpages and Quick-calcs)
Lecture 3. Multiple testing: problems and solutions
Prerequisiti
To take the Health Informatics exam, students must have already passed all the exams of the first year (Fundamentals of Basic Sciences, Cells Molecules and Genes 1 and 2, Human Body) and the exam of Functions.
To be able to fully understand the contents of the course, students must have a good knowledge of Excel. Suggested material: https://support.office.com/en-us/article/introduction-to-excel-starter-601794a9-b73d-4d04-b2d4-eed4c40f98be
To be able to fully understand the contents of the course, students must have a good knowledge of Excel. Suggested material: https://support.office.com/en-us/article/introduction-to-excel-starter-601794a9-b73d-4d04-b2d4-eed4c40f98be
Metodi didattici
Lectures by the teachers will mainly be used through the course with possible seminars from experts in Bioinformatics and ICT in medicine.
Practical activities (multiple testing problems) will be based on small student groups with discussion conducted by the teacher or by selected students.
Practical activities (multiple testing problems) will be based on small student groups with discussion conducted by the teacher or by selected students.
Materiale di riferimento
· Bland JM, Altman DG, Multiple significance tests: the Bonferroni method, BMJ 1995
· Perneger TV. What's wrong with Bonferroni adjustments. BMJ. 1998
· Ghosh D(1), Poisson LM. "Omics" data and levels of evidence for biomarker discovery. Genomics. 2009
· Other journal articles will be provided during the course
· NCBI. PubMed Help. http://www.ncbi.nlm.nih.gov/books/NBK3830/
· Santoro E, Castelnuovo G, Zoppis I, et al. Social media and mobile applications in chronic disease prevention and management. Front. Psychol., 07 May 2015
· Santoro E. Caldarola P. Villella A. Using Web 2.0 technologies and social media for the cardiologist's education and update. G Ital Cardiol 2011 Mar;12(3):174-81
· Santoro E. Web 2.0 e social media in medicina: come social network, wiki e blog trasformano la comunicazione, l'assistenza e la formazione in sanità". Il Pensiero Scientifico Editore, Roma 2011.
· Santoro E. L'intelligenza artificiale in medicina: quali limiti, quali ostacoli, quali domande. Ecenti Progressi in medicina 2017; 108: 500-502
· Topol E. The creative destruction of medicine. How the digital revolution will create better health care. Basic Books 2011
· Topol E. The Patient Will See You Now: The Future of Medicine Is in Your Hands. Basic Books 2015
· Topol E. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books 2019
· Perneger TV. What's wrong with Bonferroni adjustments. BMJ. 1998
· Ghosh D(1), Poisson LM. "Omics" data and levels of evidence for biomarker discovery. Genomics. 2009
· Other journal articles will be provided during the course
· NCBI. PubMed Help. http://www.ncbi.nlm.nih.gov/books/NBK3830/
· Santoro E, Castelnuovo G, Zoppis I, et al. Social media and mobile applications in chronic disease prevention and management. Front. Psychol., 07 May 2015
· Santoro E. Caldarola P. Villella A. Using Web 2.0 technologies and social media for the cardiologist's education and update. G Ital Cardiol 2011 Mar;12(3):174-81
· Santoro E. Web 2.0 e social media in medicina: come social network, wiki e blog trasformano la comunicazione, l'assistenza e la formazione in sanità". Il Pensiero Scientifico Editore, Roma 2011.
· Santoro E. L'intelligenza artificiale in medicina: quali limiti, quali ostacoli, quali domande. Ecenti Progressi in medicina 2017; 108: 500-502
· Topol E. The creative destruction of medicine. How the digital revolution will create better health care. Basic Books 2011
· Topol E. The Patient Will See You Now: The Future of Medicine Is in Your Hands. Basic Books 2015
· Topol E. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books 2019
Modalità di verifica dell’apprendimento e criteri di valutazione
A written test on the entire programme will be held at the end of the semester. The grades are on a scale of 30. The first and the second modules will be evaluated through closed questions. For the third module the students will be required to perform a data analysis on a small sample of observations using Excel and online calculators and fill a descriptive Table with summary data. Each module will contribute at maximum 10 points.
The exam is deemed to be passed successfully if the final grade is equal to or higher than 18/30. In the event of a full grade (30/30) honors (lode) may be granted.
Registration to the exam through SIFA is mandatory.
The exam is deemed to be passed successfully if the final grade is equal to or higher than 18/30. In the event of a full grade (30/30) honors (lode) may be granted.
Registration to the exam through SIFA is mandatory.
INF/01 - INFORMATICA - CFU: 3
Lezioni: 36 ore
Docenti:
Ambrogi Federico, Santoro Eugenio
Turni:
-
Docenti:
Ambrogi Federico, Santoro EugenioDocente/i
Ricevimento:
Su appuntamento previo contatto via e-mail
Laboratorio di Statistica Medica, Biometria ed Epidemiologia "G.A. Maccacaro", Via Celoria 22, Milano