Esse é um artigo bem antigo que escrevi em 2013, mas face aos recentes eventos na minha carreira acadêmica estou postando publicamente para ajudar quem se propõe a fazer tal tarefa.
This piece of Rajiv Shah called “Stand up for Best Practices” that involves a well known scientific journal Nature shows the academic rigor failed during several layers down and why reproducibility matters.
From MIT Tech Review article called “Google shows how AI might detect lung cancer faster and more reliably” we have the following information: Early warning: Danial Tse, a researcher at Google, developed an algorithm that beat a number of trained radiologists in testing.
Brian Resnick hit the nail in his last column in Vox called 800 scientists say it’s time to abandon “statistical significance” where he brings an important discussion in how the p-value is misleading science, especially for for the studies that has clear measurements of some particular effect but they’re thrown away because of the lack of statistical significance.
Start note: Favio Vazquez made a great job in his article about it with a lot of charts and showing that in modern Machine Learning approach with the tools that we currently have the problems of replication and methodology are being tackled.
Abstract:In the contemporary information society, constructing an effective sales prediction model is challenging due to the sizeable amount of purchasing information obtained from diverse consumer preferences.
Via O’Reilly Ideas Systematic reviews still the best method to validate (with some degree of certainty) any theory, but this is not a silver bullet.