Introduction and collaboration announcement We are thrilled to announce the official kickoff of the ZonMw Doelmatigheids research project, a pioneering initiative aimed at enhancing the treatment of anxiety and mood disorders through technology. This collaborative venture brings together Sol, Leiden University Medical Centre (LUMC), NiceDay, Depressie Vereniging, Angst Dwang en Fobie stichting, Synaeda, MiSi NeuroPsy, […]
eXplainable AI in Personalized Mental Healthcare This research collaboration aims to develop novel decision support tools for personalized online therapy by combining eXplainable Artificial Intelligence (XAI) and expert knowledge from mental healthcare professionals. Its main goal is to assist therapists during their in-between session slots by indicating which clients require close examination in their data […]
Objective and Scope This research project aims to rigorously assess the effectiveness, feasibility, and acceptability of data-supported treatments provided through the NiceDay therapy platform, specifically targeting mood and anxiety disorders. The project seeks to understand how digital therapy practices and specific factors contribute to successful treatment outcomes, laying the groundwork for extensive experimental research on […]
Kassadin-2 focuses on developing early warning technologies that can be used as decision support tool for more effective mental e-Mental Health, and providing benefits to the therapists in terms of time efficiency and service quality. Klinisch Assistentie- en Adviesplatform voor Interventies Jan 2018 – Dec 2019 Background Depression represents a significant cause of disability and […]
A technical crossover between the ICT and Health sectors aims to perform network analysis on symptoms of patients with mental complaints. This can help to focus treatments on those areas that are most crucial to the patient’s condition, leading to a more efficient treatment. Empathic Learning Infrastructure for Symptom Analysis Feb 2018 – Nov 2018 […]
Feasibility study to investigate eHealth tools that facilitate communication between practitioners and clients via chat and video calling, enriched with emotion recognition algorithms. Outcome-driven Learning Infrastructure for Multimodal Affect Recognition Apr 2018 – Feb 2019 Background Mood status is an important predictor for various mental health problems. In depression, for example, people experience long periods […]
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Introduction and collaboration announcement We are thrilled to announce the official kickoff of the ZonMw Doelmatigheids research project, a pioneering initiative aimed at enhancing the treatment of anxiety and mood disorders through technology. This collaborative venture brings together Sol, Leiden University Medical Centre (LUMC), NiceDay, Depressie Vereniging, Angst Dwang en Fobie stichting, Synaeda, MiSi NeuroPsy, […]
eXplainable AI in Personalized Mental Healthcare This research collaboration aims to develop novel decision support tools for personalized online therapy by combining eXplainable Artificial Intelligence (XAI) and expert knowledge from mental healthcare professionals. Its main goal is to assist therapists during their in-between session slots by indicating which clients require close examination in their data […]
Objective and Scope This research project aims to rigorously assess the effectiveness, feasibility, and acceptability of data-supported treatments provided through the NiceDay therapy platform, specifically targeting mood and anxiety disorders. The project seeks to understand how digital therapy practices and specific factors contribute to successful treatment outcomes, laying the groundwork for extensive experimental research on […]
Kassadin-2 focuses on developing early warning technologies that can be used as decision support tool for more effective mental e-Mental Health, and providing benefits to the therapists in terms of time efficiency and service quality. Klinisch Assistentie- en Adviesplatform voor Interventies Jan 2018 – Dec 2019 Background Depression represents a significant cause of disability and […]
A technical crossover between the ICT and Health sectors aims to perform network analysis on symptoms of patients with mental complaints. This can help to focus treatments on those areas that are most crucial to the patient’s condition, leading to a more efficient treatment. Empathic Learning Infrastructure for Symptom Analysis Feb 2018 – Nov 2018 […]
Feasibility study to investigate eHealth tools that facilitate communication between practitioners and clients via chat and video calling, enriched with emotion recognition algorithms. Outcome-driven Learning Infrastructure for Multimodal Affect Recognition Apr 2018 – Feb 2019 Background Mood status is an important predictor for various mental health problems. In depression, for example, people experience long periods […]
