Validity of machine learning in biology and medicine increased through collaborations across fields of expertise.
Maria LittmannKatharina SeligLiel Cohen-LaviYotam FrankPeter HönigschmidEvans KatakaAnja MöschKun QianAvihai RonSebastian SchmidAdam SorbieLiran SzlakAyana Dagan-WienerNir Ben-TalMasha Y. NivDaniel RazanskyBjörn W. SchullerDonna P. AnkerstTomer HertzBurkhard RostPublished in: Nat. Mach. Intell. (2020)
Keyphrases
- machine learning
- computational biology
- seemingly unrelated
- computer vision
- data mining
- medical domain
- diverse fields
- decision trees
- pattern recognition
- artificial intelligence
- molecular biology
- learning tasks
- machine learning methods
- interdisciplinary field
- explanation based learning
- machine learning approaches
- natural language processing
- semi supervised learning
- machine learning algorithms
- knowledge acquisition
- scientific fields
- natural language
- biomedical engineering
- computer science
- machine learning and data mining
- data analysis
- real time
- model selection
- learning algorithm
- expert systems
- supervised learning
- inductive learning
- inductive logic programming
- learning problems
- medical images
- learning systems