Why it is a problem and a benchmark to find a solution

By Karina Zadorozhny and Giovanni Cinà (Pacmed Labs)

This blogpost is for you if: you are interested in deploying medical AI in real-world contexts.

Introduction

As Machine Learning is poised to revolutionize healthcare, we need to pause and think about all the possible ways in which our super-performing models may not work well in practice. One key reason for this is the fact that real live data may differ from training data, namely the data that the model has learned from. …


By Giovanni Cinà (Pacmed Labs)

This blog post is for you if: you work in healthcare, you are interested in AI, you are binge-reading content on COVID-19 while splayed on the couch.

Intro

At the time of writing, it has been more than a year since the onset of the COVID-19 pandemic. Among all the ways in which our lives have been changed, we have all been presented with a very pressing question: how do we find a cure?

The problem of finding effective medications and vaccines, an issue that used to concern only a restricted group of experts, suddenly took…


Door Wouter Kroese op Emerce

Het menselijk lichaam is ontzettend complex. Tien biljoen cellen, aangestuurd door een genoom van drie miljard letters, vele honderden ingewikkelde processen en een brein dat we nog maar voor een heel klein deel begrijpen. Nog complexer is het genezen van dit lichaam als er ergens iets mis gaat.

Er is, zeker in Nederland, ontzettend veel kennis over ziektes en behandelingen. Als zorgverlener wil je echter vooral het leven van die specifieke patiënt aan het bed of tegenover je beter maken. …


By Giovanni Cinà and Michele Tonutti (Data Scientists at Pacmed)

Helping doctors and data scientists get a clear view on the latest developments in medical AI

As AI agents grow in skills and complexity, the interaction between humans and machines becomes more important than ever. The true added value seems not to lie in Artificial Intelligence alone, but in the synergy between human and technology. Understanding well how the technology operates is key to the facilitation of this synergy. How can we understand and trust the decisions or predictions of an artificial intelligence? This question is even more pressing in the medical domain, where AI can directly influence the health of many.

In this issue of…


By Michele Tonutti, Data Scientist at Pacmed

“Will writing tidy code really help patients when they are rushed into the Intensive Care Unit?”

“Who cares if my code is 100 or 1 billion lines long, if the doctor will only see a probability and a graph?”

“If in order to test my code I need to write more code, do I just keep writing code forever to test the tests?”

These (and many other) questions have probably, in one form or another, popped into the mind of all beginner coders who have started a project in medical data science. …


By Aleide Hoeijmakers and Pim Hoeven

After six months of working hard and having a lot of fun, our internship at Pacmed has unfortunately come to an end. In this blog we will share our experiences as interns at Pacmed; for students who are thinking about doing their internships at a company (instead of a university) but also for anyone else who is interested! We will first shortly describe our projects followed by some more general aspects of interning at Pacmed, followed by some practical tips!

Why Pacmed
We chose to do our internship at Pacmed for similar reasons: to learn…


By Michele Tonutti, Data Scientist at Pacmed

How would you feel knowing that the quality of every single line of your code will directly impact the lives of thousands of people?

Anyone who has ever coded even a simple script has likely experienced the pure excitement of seeing their program run for the first time without errors. For Data Scientists in particular, the satisfaction of successfully building and training a machine learning model is probably unrivalled.

This is particularly true in medical data science: the thrill of data-driven problem solving is exponentially amplified by the awareness that the predictions of…


door Daan de Bruin (Pacmed)

Als ik vertel over ons werk op het gebied van prostaatkanker, gebeurt het me opvallend vaak dat mensen persoonlijk geraakt zijn door dit onderwerp. Laatst vertelde iemand me: “Mijn vader is overleden aan prostaatkanker. Toen de arts de gemiddelde verwachte overlevingskansen aan ons liet zien, vroeg ik me af in hoeverre die toepasbaar waren op de situatie waar mijn vader zich in bevond.” Kan dit niet slimmer?

Lees het hele artikel hier:


By Giovanni Cinà and Michele Tonutti (Data Scientists at Pacmed)

Helping doctors and data scientists get a clear view on the latest developments in medical AI

Machine learning promises to be a technology that could help medical professionals and patients to achieve better health outcomes. This value does not come easily, and the implementation of machine learning in healthcare is a precarious issue. There should be constant consideration of the boundary conditions under which it must be implemented in order to be of sustainable and scalable value for everyone. Machine learning is not good and safe by definition, and responsible deployment is the key to success for the patient. There are risks of empty correlations, biases…


Door Daan de Bruin, september 2018

Wat is het beste antidepressivum voor een bepaalde patiënt? Psychiaters staan dagelijks voor deze vraag en de beslissing kan grote impact hebben op de levens van depressieve patiënten. Om behandelkeuzes meer gepersonaliseerd te kunnen maken, hebben het UMC Utrecht en Pacmed modellen ontwikkeld die de effectiviteit van verschillende antidepressiva voorspellen voor patiënten met een ernstige depressie. De modellen hebben veelbelovende resultaten, maar meer onderzoek is nodig.

Lees het hele artikel hier:

https://tech.qruxx.com/onderzoek-gepersonaliseerde-behandeling-van-depressies/

Pacmed

Pacmed builds decision support tools for doctors based on machine learning that makes sure patients only receive care that has proven to work for them!

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store