Nursing REPLICA ASL ROMA 3 - OSTIA

INFORMATION PROCESSING SYSTEMS · Computer Science and Data o What is computer science o Difference between data and information o The DIKW Pyramid (Data, Information, Knowledge, Wisdom) o Types of data: qualitative vs quantitative, simple vs complex · Automatic Processing and Health Information Systems o Information processing cycle o The New National Health Information System (NSIS) o Health information flows and their importance · Tools for Data Processing: Excel (1 hour) o Tables, formulas, cell references o Statistical functions (COUNT, AVERAGE, STDEV, etc.) o Sorting and filters o Introduction to pivot tables (example with health data) · Introduction to Artificial Intelligence o What is AI? Definition and historical notes o Weak AI vs Strong AI o Examples of AI in everyday life and healthcare o Brief mention of machine learning · Databases and Data Management o Types of databases: flat-file, relational, object-oriented o Tables, keys, relationships (1:n, n:m) o Examples with Microsoft Access o Importance of DBMS in healthcare · Descriptive Statistics with Excel o Frequency distributions o Measures of central tendency (mean, median, mode) o Measures of dispersion (variance, standard deviation) o Graphical representations: histograms, box plots o Using Excel's Data Analysis toolpak · Artificial Intelligence in Healthcare o Machine Learning: supervised vs unsupervised o Examples of AI in diagnostics (CT scan image analysis, MRI) o AI for predicting epidemics or hospital readmissions o Natural Language Processing (NLP) for medical records o Ethical considerations: transparency, bias, privacy · Practical Exercise: Health Data and AI o Analysis of a simulated health dataset with Excel o Application of filters, pivot tables, and calculation of indicators o Guided discussion: how AI could improve the analysis