Published inLunit Team BlogHow Lunit hires top AI talentHiring is really important in any company. The people you hire will determine what the company will look like a few years down the road and…Jan 17, 20231Jan 17, 20231
Published inLunit Team BlogMICCAI tutorial on AI for medical image analysis in practiceAI in practiceJul 18, 2022Jul 18, 2022
Published inLunit Team BlogEvaluation curves for object detection algorithms in medical imagesSafety critical applications of artificial intelligence, like computer aided detection; the detection of abnormalities in medical images…Nov 3, 2021Nov 3, 2021
Published inLunit Team BlogPhotometric data augmentation in projection radiographyFor artificial intelligence to be widely applied to a variety of problems, building specific systems for all possible niche problems does…Apr 16, 20211Apr 16, 20211
Published inLunit Team BlogCognitive biases and augmented intelligence in radiologyHow cognitive biases affect diagnostic problems in radiology and how AI can help outAug 2, 2020Aug 2, 2020
Published inTowards Data ScienceUnderstanding breast cancer screening dataHow the epidemiological basis of data can be used to better train and understand AI modelsJun 2, 2020Jun 2, 2020
Published inmerantixDeep learning: From natural to medical imagesHow to adjust deep neural networks to medical image analysis problemsDec 19, 2018Dec 19, 2018
Published inmerantixThe long tail of medical dataPower law distributions and computer aided diagnosisOct 25, 2018Oct 25, 2018
