چتبات تعاملی درس آمار زیستی (Medical Statistics) برای دانشجویان این درس توسعه یافته و در اختیار آنان قرار گرفته است. این سامانه به منظور پشتیبانی آموزشی، پاسخگویی به سؤالات مفهومی و کاربردی، و ارتقای یادگیری فعال طراحی شده است.
منابع و مراجع معتبر مورد استفاده در طراحی این چتبات شامل کتابها و منابع علمی اصلی درس آمار زیستی هستند که از میان آنها میتوان به موارد زیر اشاره کرد: Kuncheva LI. Combining Pattern Classifiers: Methods and Algorithms. 2nd ed. Hoboken (NJ): John Wiley & Sons; 2014.
King AP, Eckersley RJ. Statistics for Biomedical Engineers and Scientists: How to Visualize and Analyze Data. Cambridge (MA): Academic Press/Elsevier; 2019
. Steyerberg EW. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. 2nd ed. Cham (Switzerland): Springer Nature; 201
9. Ross SM. Introduction to Probability and Statistics for Engineers and Scientists. 6th ed. London: Academic Press/Elsevier; 20
21. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates; 1
988. Machin D, Campbell MJ, Tan SB, Tan SH. Sample Size Tables for Clinical Studies. 3rd ed. Chichester (UK): Wiley-Blackwell;
2009. Julious SA. Sample Sizes for Clinical Trials. 2nd ed. Boca Raton (FL): CRC Press;
2023. Colquhoun D. An investigation of the false discovery rate and the misinterpretation of p-values. R Soc Open Sci. 2014;1:
140216. Van Calster B, McLernon DJ, van Smeden M, Wynants L, Steyerberg EW. Calibration: the Achilles heel of predictive analytics. BMC Med. 2019
;17:230. Dietterich TG. Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput. 1998;10(7):1
895-1923. International Organization for Standardization (ISO). ISO 14155:2020. Clinical investigation of medical devices for human subjects — Good clinical practice. Geneva:
ISO; 2020. International Organization for Standardization/International Electrotechnical Commission (ISO/IEC). ISO/IEC 23894:2023. Information technology — Artificial intelligence — Guidance on risk management. Geneva: ISO
/IEC; 2023. ISO/IEC. TR 24028:2020. Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence. Geneva: IS
O/IEC; 2020. ISO/IEC. TR 24027:2021. Information technology (AI) — Bias in AI systems and AI-aided decision making. Geneva: I
SO/IEC; 2021. ISO/IEC. TR 24029-1:2021. Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview. Geneva:
ISO/IEC; 2021. ISO/IEC. DIS 24029-2:2022. Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 2: Methodology for the use of formal methods. Geneva: ISO/IEC; 2022. Draft Internat
ional Standard. ISO/IEC. TS 4213:2022. Information technology — Artificial intelligence — Assessment of machine learning classification performance. Geneva
: ISO/IEC; 2022. ISO/IEC. TS 12791:2024. Information technology — Artificial intelligence — Treatment of unwanted bias in classification and regression machine learning tasks. Geneva: ISO/IEC; 2024. (Adopted as CEN/CLC ISO/IE
C/TS 12791:2024.) Steyerberg EW, Vergouwe Y. Seven steps to model development and validation (case study from GUSTO-I). Eur Heart J. 2014;35(29):1925-1931. doi:10.1093
/eurheartj/ehu207. Ross SM. Introduction to Probability and Statistics for Engineers and Scientists. 6th ed. Academic Press; 2021. (ISBN
978-0-12-824346-6). چتبات مذکور به صورت ۲۴ ساعت در شبانهروز و ۷ روز هفته فعال بوده و در دسترس تمامی دانشجویان این درس میباشد.
با آرزوی موفقیت برای همه دانشجویان گرامی
دکتر حمیدرضا مراتب
عضو هیأت علمی گروه مهندسی پزشکی
دانشکده مهندسی، دانشگاه اصفهان
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