Vor Memmo waren meine Notizen überall in PDFs verstreut. Jetzt sammelt ein Arbeitsbereich alles an einem Ort – ich sehe genau, was noch zu lernen ist.
Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB® toolbox for the collection, visualization, and evaluation of experimental and real-life data
Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® presents a practical approach to the task that biological scientists face when analyzing data. The primary focus is on the application of mathematical models and scientific computing methods to provide insight into the behavior of biological systems. The author draws upon his experience in academia, industry, and government–sponsored research as well as his expertise in MATLAB to produce a suite of computer programs with applications in epidemiology, machine learning, and biostatistics. These models are derived from real–world data and concerns. Among the topics included are the spread of infectious disease (HIV/AIDS) through a population, statistical pattern recognition methods to determine the presence of disease in a diagnostic sample, and the fundamentals of hypothesis testing.
In addition, the author uses his professional experiences to present unique case studies whose analyses provide detailed insights into biological systems and the problems inherent in their examination. The book contains a well-developed and tested set of MATLAB functions that act as a general toolbox for practitioners of quantitative biology and biostatistics. This combination of MATLAB functions and practical tips amplifies the book’s technical merit and value to industry professionals.
Through numerous examples and sample code blocks, the book provides readers with illustrations of MATLAB programming. Moreover, the associated toolbox permits readers to engage in the process of data analysis without needing to delve deeply into the mathematical theory. This gives an accessible view of the material for readers with varied backgrounds. As a result, the book provides a streamlined framework for the development of mathematical models, algorithms, and the corresponding computer code.
In addition, the book features:
Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® is an excellent textbook for students in mathematics, biostatistics, the life and social sciences, and quantitative, computational, and mathematical biology. This book is also an ideal reference for industrial scientists, biostatisticians, product development scientists, and practitioners who use mathematical models of biological systems in biomedical research, medical device development, and pharmaceutical submissions.
Vor Memmo waren meine Notizen überall in PDFs verstreut. Jetzt sammelt ein Arbeitsbereich alles an einem Ort – ich sehe genau, was noch zu lernen ist.
Memmos Zusammenfassungen sind Gold wert vor Prüfungen. Ich muss nicht zwei Wochen vorher 800 Seiten neu lesen – nur die wichtigsten Teile.
Der KI-Chat hat mich schon mehr als einmal am Abend vor einer Prüfung gerettet. Ich frage einfach so lange, bis ich es kapiere – ohne auf eine Antwort in einer Lerngruppe warten zu müssen.
Die Quizzes treffen genau das, was ich wissen muss. Memmo merkt sich, wo ich Schwierigkeiten habe – so übe ich nur das, was sich lohnt.
Lernkarten mit Spaced Repetition sind Magie. Memmo weiß, wann ich etwas vergessen könnte und zeigt es mir wieder.
Die KI-Podcasts sind mein Favorit. Ich höre sie auf dem Weg zur Uni und bekomme eine Wiederholung, ohne am Computer sitzen zu müssen.
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