< Back to news ![CuspAI Introduces Itself at LAB42](/Cusp_ai.jpg?version=4136)
![Advanced AI for Surveillance Robots: A Collaborative Project by Dutch Institutions](/cees_nieuw_loab.jpg?version=4132)
![NeuroAI: Charlotte Frenkel explores the future of AI inspired by the human brain](/AINED.jpg?version=852)
9 February 2024
AI Technology Revolutionizes Antidepressant Treatment
Research led by Amsterdam UMC and Radboudumc has unveiled a groundbreaking advancement in the treatment of major depression disorder. Utilizing artificial intelligence (AI), researchers have developed a method to predict the effectiveness of antidepressants within just one week, significantly shortening the traditional six to eight-week waiting period.
Published in the esteemed American Journal of Psychiatry, the study marks a pivotal moment in mental health care. Professor Liesbeth Reneman, a leading figure in neuroradiology at Amsterdam UMC, emphasizes the significance of this breakthrough: "This is transformative for patients, offering a swift insight into the efficacy of antidepressants, which typically remains uncertain for weeks."
The research team focused their analysis on sertraline, the most commonly prescribed antidepressant in the United States. By examining MRI scans and clinical data from 229 patients, they developed an AI algorithm that accurately predicted treatment outcomes. Remarkably, the algorithm identified that sertraline was effective for only one-third of patients, allowing psychiatrists to tailor treatment plans accordingly and minimize unnecessary prescriptions.
Dr. Eric Ruhé, a psychiatrist at Radboudumc, elaborates on the algorithm's predictive power: "Our findings highlight the significance of brain activity patterns, particularly in the anterior cingulate cortex, in determining treatment response. This enables clinicians to swiftly identify suitable candidates for sertraline therapy."
Looking ahead, this pioneering method holds promise for personalized antidepressant treatment, potentially alleviating the prolonged trial-and-error process endured by patients. With further refinement, the algorithm could revolutionize depression management, offering a more efficient and effective approach to care.
As depression continues to pose a significant societal challenge, with one in three patients experiencing persistent symptoms despite multiple treatment attempts, the need for expedited and precise treatment strategies has never been more urgent. With ongoing research efforts to enhance the algorithm's predictive capabilities, the future of depression treatment looks increasingly promising. Stay tuned for updates as we navigate towards a brighter future in mental health care.
Read it here.
This article has been published on the website of Amsterdam UMC.
Vergelijkbaar >
Similar news items
![CuspAI Introduces Itself at LAB42](/Cusp_ai.jpg?version=4136)
6 September 2024
CuspAI Introduces Itself at LAB42
On September 5, 2024, Max Welling and Chad Edwards, founders of CuspAI, presented their innovative company during the IvI coffee & cake gathering.
read more >
![Advanced AI for Surveillance Robots: A Collaborative Project by Dutch Institutions](/cees_nieuw_loab.jpg?version=4132)
5 September 2024
Advanced AI for Surveillance Robots: A Collaborative Project by Dutch Institutions
A consortium of leading Dutch research institutions and government agencies, including TU Delft, the University of Amsterdam, TNO, and the Royal Netherlands Marechaussee, has launched an ambitious project aimed at developing advanced artificial intelligence (AI) for surveillance robots. Officially initiated on September 4, the OpenBots consortium focuses on creating AI systems designed to assist human security officers in various security settings.
read more >
![NeuroAI: Charlotte Frenkel explores the future of AI inspired by the human brain](/AINED.jpg?version=852)
September 5, 2024
NeuroAI: Charlotte Frenkel explores the future of AI inspired by the human brain
With the award of an AiNed Fellowship grant, Dr. Charlotte Frenkel from TU Delft delves into neuromorphic computing, pioneering research aimed at creating energy-efficient and powerful AI systems inspired by the human brain. This research bridges AI and neuroscience to develop faster, more energy-efficient, and smarter computing systems.
read more >