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Everything about Biomedical data science

Analysis of large datasets to understand living systems

Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics, Biomedical informatics, and machine learning, with the goal of understanding biological and medical data. It can be viewed as the study and application of data science to solve biomedical problems. Modern biomedical datasets often have specific features which make their analyses difficult, including:Large numbers of feature, typically far larger than the number of samples Noisy and missing data Privacy concerns Requirement of interpretability from decision makers and regulatory bodies Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Biomedical data scienceA 5-minute orientation
  2. Skim a recent paper: Privacy-Enhancing Technologies in Biomedical Data ScienceInfluential work since 2022
  3. Pick up a classic book: Ambient Assisted LivingThe most-reprinted book on the subject
  4. Read the landmark paper: Network embedding in biomedical data scienceCited 150 times
  5. Go sideways: Translational bioinformaticsA closely related topic
  6. Go sideways: Computational epigeneticsA closely related topic

📖 Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. Computational Imaging and Deep Learning
  2. Electronic Health Records
  3. Artificial Intelligence and Machine Learning Applications
  4. Knowledge Graphs
  5. Privacy
  6. Training in Biomedical Data Science
  7. Biomedical Data Science Research in Academia
  8. Genomic Data Science

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics